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Contract & Proposal Writer · thomasmoreai | DecimalAI

Legalby thomasmoreai

Contract & Proposal Writer

Generate production-ready business documents including freelance contracts, project proposals, SOWs, NDAs, and MSAs with jurisdiction-aware clauses. Covers US (Delaware), EU (GDPR), UK, and DACH (German law) legal frameworks. Includes contract templates, clause libraries, and DOCX conversion.

SkillScore

SkillScore77/100

Test results 77

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

45%77%of test cases passed +32 pts

Without skill10 of 22

With skill17 of 22

9 fixed8 passed either way3 still failing2 broke

Measured on gemini-3.6-flash8/5/2026v121 comparable

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskShow the exact terminal command invocation to run a CLI verification check on a German agreement file named service_agreement.json using the contract verification script for DACH jurisdiction and hourly engagement type, returning structured JSON.

Without the skillMissed

With the skillPassed

Same model, same task. Answers are capped and redacted.

Use this skill

Your agent runs on

Adds every file the skill has, pinned so you can update it. No account needed.

pip install "decimalai>=0.15"
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei
claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"

The same install from Python, for a notebook or a setup script.

Install

pip install "decimalai>=0.15"

Add the skill

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("thomasmoreai-contract-and-proposal-writer-borghei")
if result.exit_code:
    raise SystemExit(result.problems)

print("Added. Start Claude Code with the command below.")

Start Claude Code with it

claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"

Type these in a Claude Code session. No account or API key. It writes the skill and any files it bundles, and asks first when its safety rating isn't Passed.

Add the DecimalAI plugin, once

/plugin marketplace add decimal-labs/decimalai-claude-plugins
/plugin install decimalai@decimalai

Install this skill

/decimalai:install thomasmoreai-contract-and-proposal-writer-borghei

The plugin needs python3 and curl on your machine.

No Python or account. Claude Code picks it up in its next session.

Save it into your project

curl -fsSL --create-dirs -o .claude/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md https://app.decimal.ai/s/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

Claude Code docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[claude-agent-sdk]"
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei

Add it to your agent

import asyncio

from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

async def main():
    question = "Hello!"
    async with support.run(question) as run:  # one user message, one run
        async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
            print(message)

# In a notebook or async code: await main()
asyncio.run(main())

Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[claude-agent-sdk]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("thomasmoreai-contract-and-proposal-writer-borghei")
if result.exit_code:
    raise SystemExit(result.problems)

import asyncio

from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

async def main():
    question = "Hello!"
    async with support.run(question) as run:  # one user message, one run
        async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
            print(message)

# In a notebook or async code: await main()
asyncio.run(main())

Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from claude_agent_sdk import ClaudeAgentOptions, query

skill = Path(".agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md").read_text()
options = ClaudeAgentOptions(system_prompt=f"You are a helpful agent.\n\n{skill}", max_turns=6)

async def main():
    async for message in query(prompt="Hello!", options=options):
        print(message)

# In a notebook or async code: await main()
asyncio.run(main())

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

Claude Agent SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai-agents]"
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei

Add it to your agent

from agents import Agent, Runner
from decimalai.openai_agents import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    name=support.name,
    instructions=support.instructions,  # your prompt, then the skill list
    tools=[*support.tools],             # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.

Install

pip install "decimalai[openai-agents]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("thomasmoreai-contract-and-proposal-writer-borghei")
if result.exit_code:
    raise SystemExit(result.problems)

from agents import Agent, Runner
from decimalai.openai_agents import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    name=support.name,
    instructions=support.instructions,  # your prompt, then the skill list
    tools=[*support.tools],             # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md").read_text()
agent = Agent(name="support", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

OpenAI Agents docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai]"
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei

Add it to your agent

import json

from openai import OpenAI
from decimalai.openai import agent_config

client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
                   "required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    # run.system is your prompt, then the skill list.
    messages = [{"role": "system", "content": run.system}, run.message]
    while True:
        reply = client.chat.completions.create(
            model="gpt-5.4-mini",
            messages=messages,
            tools=[*TOOLS, *run.tools],  # your tools, then load_skill
        ).choices[0].message
        messages.append(reply)
        if not reply.tool_calls:
            break
        for call in reply.tool_calls:
            # load_skill is answered by the run; your own tools by FUNCTIONS.
            function = FUNCTIONS.get(call.function.name)
            messages.append(run.tool_result(call) or {
                "role": "tool", "tool_call_id": call.id,
                "content": function(**json.loads(call.function.arguments)) if function
                else f"There is no tool named {call.function.name!r}.",
            })
print(reply.content)

# The Responses API takes run.response_tools instead of run.tools.

Install

pip install "decimalai[openai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("thomasmoreai-contract-and-proposal-writer-borghei")
if result.exit_code:
    raise SystemExit(result.problems)

import json

from openai import OpenAI
from decimalai.openai import agent_config

client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
                   "required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    # run.system is your prompt, then the skill list.
    messages = [{"role": "system", "content": run.system}, run.message]
    while True:
        reply = client.chat.completions.create(
            model="gpt-5.4-mini",
            messages=messages,
            tools=[*TOOLS, *run.tools],  # your tools, then load_skill
        ).choices[0].message
        messages.append(reply)
        if not reply.tool_calls:
            break
        for call in reply.tool_calls:
            # load_skill is answered by the run; your own tools by FUNCTIONS.
            function = FUNCTIONS.get(call.function.name)
            messages.append(run.tool_result(call) or {
                "role": "tool", "tool_call_id": call.id,
                "content": function(**json.loads(call.function.arguments)) if function
                else f"There is no tool named {call.function.name!r}.",
            })
print(reply.content)

# The Responses API takes run.response_tools instead of run.tools.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md").read_text()
reply = client.chat.completions.create(
    model="gpt-5.4-mini",
    messages=[
        {"role": "system", "content": f"You are a helpful agent.\n\n{skill}"},
        {"role": "user", "content": "Hello!"},
    ],
).choices[0].message

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

OpenAI SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[anthropic]"
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei

Add it to your agent

import anthropic
from decimalai.anthropic import agent_config

client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

question = "Hello!"
with support.run(question) as run:  # one user message, one run
    answer = client.beta.messages.tool_runner(
        model="claude-haiku-5-5",
        max_tokens=4096,
        system=run.system,     # your prompt, then the skill list
        tools=[*run.tools],    # your tools, then load_skill
        messages=[{"role": "user", "content": question}],
    ).until_done()

Install

pip install "decimalai[anthropic]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("thomasmoreai-contract-and-proposal-writer-borghei")
if result.exit_code:
    raise SystemExit(result.problems)

import anthropic
from decimalai.anthropic import agent_config

client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

question = "Hello!"
with support.run(question) as run:  # one user message, one run
    answer = client.beta.messages.tool_runner(
        model="claude-haiku-5-5",
        max_tokens=4096,
        system=run.system,     # your prompt, then the skill list
        tools=[*run.tools],    # your tools, then load_skill
        messages=[{"role": "user", "content": question}],
    ).until_done()

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md").read_text()
reply = client.messages.create(
    model="claude-haiku-5-5",
    max_tokens=4096,
    system=f"You are a helpful agent.\n\n{skill}",
    messages=[{"role": "user", "content": "Hello!"}],
)

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

Anthropic docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[google-genai]"
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei

Add it to your agent

from google import genai
from google.genai import types
from decimalai.google_genai import agent_config

client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
                               "required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    config = types.GenerateContentConfig(
        system_instruction=run.system,     # your prompt, then the skill list
        tools=[*TOOLS, *run.tool_params],  # your functions, then load_skill
    )
    contents = [{"role": "user", "parts": [{"text": run.message}]}]
    while True:
        response = client.models.generate_content(
            model="gemini-3.5-flash", contents=contents, config=config,
        )
        if not response.function_calls:
            break
        contents.append(response.candidates[0].content)
        parts = []
        for call in response.function_calls:
            # load_skill is answered by the run; your own functions by FUNCTIONS.
            # A loop of your own rather than automatic function calling, which
            # raises KeyError when the model asks for a function you did not pass.
            function = FUNCTIONS.get(call.name)
            parts.append(run.tool_result(call) or {"function_response": {
                "name": call.name, "id": call.id,
                "response": {"result": function(**(call.args or {})) if function
                             else f"There is no function named {call.name!r}."},
            }})
        contents.append({"role": "user", "parts": parts})
print(response.text)

Install

pip install "decimalai[google-genai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("thomasmoreai-contract-and-proposal-writer-borghei")
if result.exit_code:
    raise SystemExit(result.problems)

from google import genai
from google.genai import types
from decimalai.google_genai import agent_config

client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
                               "required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    config = types.GenerateContentConfig(
        system_instruction=run.system,     # your prompt, then the skill list
        tools=[*TOOLS, *run.tool_params],  # your functions, then load_skill
    )
    contents = [{"role": "user", "parts": [{"text": run.message}]}]
    while True:
        response = client.models.generate_content(
            model="gemini-3.5-flash", contents=contents, config=config,
        )
        if not response.function_calls:
            break
        contents.append(response.candidates[0].content)
        parts = []
        for call in response.function_calls:
            # load_skill is answered by the run; your own functions by FUNCTIONS.
            # A loop of your own rather than automatic function calling, which
            # raises KeyError when the model asks for a function you did not pass.
            function = FUNCTIONS.get(call.name)
            parts.append(run.tool_result(call) or {"function_response": {
                "name": call.name, "id": call.id,
                "response": {"result": function(**(call.args or {})) if function
                             else f"There is no function named {call.name!r}."},
            }})
        contents.append({"role": "user", "parts": parts})
print(response.text)

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Give it to your agent

from pathlib import Path
from google import genai
from google.genai import types

client = genai.Client()
skill = Path(".agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md").read_text()
response = client.models.generate_content(
    model="gemini-3.5-flash",
    contents="Hello!",
    config=types.GenerateContentConfig(system_instruction=f"You are a helpful agent.\n\n{skill}"),
)

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

Gemini API docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[langchain]" langchain-openai
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei

Add it to your agent

from langchain.agents import create_agent
from decimalai.langchain import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = create_agent(
    "openai:gpt-5.4-mini",
    tools=[],                         # your tools; the middleware adds load_skill
    middleware=[support.middleware],  # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

Install

pip install "decimalai[langchain]" langchain-openai

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("thomasmoreai-contract-and-proposal-writer-borghei")
if result.exit_code:
    raise SystemExit(result.problems)

from langchain.agents import create_agent
from decimalai.langchain import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = create_agent(
    "openai:gpt-5.4-mini",
    tools=[],                         # your tools; the middleware adds load_skill
    middleware=[support.middleware],  # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md").read_text()
agent = create_agent("openai:gpt-5.4-mini", tools=[], system_prompt=f"You are a helpful agent.\n\n{skill}")
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

LangChain docs

CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei

Add it to your agent

import decimalai.crewai
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                               # your own CrewAI LLM
    skills=decimalai.crewai.skills(),      # the installed folder
    tools=decimalai.crewai.skill_tools(),  # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

The same install from Python, for a notebook or a setup script. CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("thomasmoreai-contract-and-proposal-writer-borghei")
if result.exit_code:
    raise SystemExit(result.problems)

import decimalai.crewai
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                               # your own CrewAI LLM
    skills=decimalai.crewai.skills(),      # the installed folder
    tools=decimalai.crewai.skill_tools(),  # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

No DecimalAI package. CrewAI's own loader reads the folder, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Give it to your agent

from pathlib import Path
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                         # your own CrewAI LLM
    skills=[Path(".agents/skills")],
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

CrewAI docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[adk]"
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei

Add it to your agent

from decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = LlmAgent(
    name="support",          # ADK needs a Python identifier
    model="gemini-3.5-flash",
    instruction=support.instruction,  # your prompt, then the skill list
    tools=[*support.tools],           # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])

Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

Install

pip install "decimalai[adk]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("thomasmoreai-contract-and-proposal-writer-borghei")
if result.exit_code:
    raise SystemExit(result.problems)

from decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = LlmAgent(
    name="support",          # ADK needs a Python identifier
    model="gemini-3.5-flash",
    instruction=support.instruction,  # your prompt, then the skill list
    tools=[*support.tools],           # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])

Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Give it to your agent

from pathlib import Path
from google.adk.agents import LlmAgent

skill = Path(".agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md").read_text()
agent = LlmAgent(
    name="support",
    model="gemini-3.5-flash",
    instruction=lambda context: f"You are a helpful agent.\n\n{skill}",
)

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

Google ADK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[pydantic-ai]"
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei

Add it to your agent

from pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    "openai:gpt-4o-mini",
    name=support.name,
    tools=[],                 # your tools; the capability adds load_skill
    capabilities=[support],   # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.

Install

pip install "decimalai[pydantic-ai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("thomasmoreai-contract-and-proposal-writer-borghei")
if result.exit_code:
    raise SystemExit(result.problems)

from pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    "openai:gpt-4o-mini",
    name=support.name,
    tools=[],                 # your tools; the capability adds load_skill
    capabilities=[support],   # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md").read_text()
agent = Agent("openai:gpt-4o-mini", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

Pydantic AI docs

Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" deepagents
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei

Add it to your agent

import decimalai.deepagents
from deepagents import create_deep_agent

agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).

The same install from Python, for a notebook or a setup script. Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" deepagents

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("thomasmoreai-contract-and-proposal-writer-borghei")
if result.exit_code:
    raise SystemExit(result.problems)

import decimalai.deepagents
from deepagents import create_deep_agent

agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md").read_text()
agent = create_deep_agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

Deep Agents docs

Its own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" agent-framework
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei

Add it to your agent

import asyncio

from agent_framework import Agent
from decimalai.agent_framework import skills

agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))

It caches skills by default, so restart the process after decimalai skills update.

The same install from Python, for a notebook or a setup script. Its own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" agent-framework

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("thomasmoreai-contract-and-proposal-writer-borghei")
if result.exit_code:
    raise SystemExit(result.problems)

import asyncio

from agent_framework import Agent
from decimalai.agent_framework import skills

agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))

It caches skills by default, so restart the process after decimalai skills update.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md").read_text()
agent = Agent(client=client, instructions=f"You are a helpful agent.\n\n{skill}")
asyncio.run(agent.run("Hello!"))

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

Microsoft Agent Framework docs

Strands' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" strands-agents
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei

Add it to your agent

from decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell

agent = Agent(
    model=model,                # always pass one: the default is Amazon Bedrock
    system_prompt="You are a helpful agent.",
    tools=[file_editor, shell],
    plugins=[skills()],
)
agent("Hello!")

Strands loads an agent's skills once, so build the agent again after decimalai skills update.

The same install from Python, for a notebook or a setup script. Strands' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" strands-agents

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("thomasmoreai-contract-and-proposal-writer-borghei")
if result.exit_code:
    raise SystemExit(result.problems)

from decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell

agent = Agent(
    model=model,                # always pass one: the default is Amazon Bedrock
    system_prompt="You are a helpful agent.",
    tools=[file_editor, shell],
    plugins=[skills()],
)
agent("Hello!")

Strands loads an agent's skills once, so build the agent again after decimalai skills update.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md").read_text()
agent = Agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent("Hello!")

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

Strands docs

Adds every file the skill has, pinned so you can update it. Cursor, Copilot, Cline and Warp read this folder by themselves.

pip install "decimalai>=0.15"
decimalai skills add thomasmoreai-contract-and-proposal-writer-borghei

No Python or account. Cursor, Copilot, Cline and Warp read this folder by themselves.

Save it into your project

curl -fsSL --create-dirs -o .agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md https://app.decimal.ai/s/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

Cursor and other editors docs

Fetch the file and give its text to your model as instructions. No account or package needed.

Get the file

curl -fsSL https://app.decimal.ai/s/thomasmoreai-contract-and-proposal-writer-borghei/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/thomasmoreai-contract-and-proposal-writer-borghei.json

This gets SKILL.md only. The skill's 3 other files are not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v1, tested 8/5/2026
Source: thomasmoreai/legal-skills-open ↗
License: Apache-2.0

Manage it in DecimalAI

Saved prompts and skills, pinned versions, and traces of this skill in your runs. DecimalAI does not run your agent.

Claude Code reads files from your project, so DecimalAI config does not apply there.

On Claude Agent SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI Agents: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Anthropic: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Gemini API: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On LangChain: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On CrewAI: set DECIMAL_API_KEY and add decimalai.init(crewai=True) to record runs and skill use. The skill version stays in your repo.

On Google ADK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Pydantic AI: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Deep Agents: set DECIMAL_API_KEY and add decimalai.init(langchain=True) to record runs and skill use. The skill version stays in your repo.

On Microsoft Agent Framework: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

On Strands: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

Editors read files from your project, so DecimalAI config does not apply there.

Anywhere else: record a use with decimalai.log_skill_activation() inside a trace.

Use this skill

SKILL.md

Contract & Proposal Writer

Tier: POWERFUL Category: Business Growth Tags: contracts, proposals, SOW, NDA, MSA, GDPR, legal templates, freelance

Overview

Generate professional, jurisdiction-aware business documents: freelance contracts, project proposals, statements of work, NDAs, and master service agreements. Outputs structured Markdown with conversion instructions for DOCX and PDF. Covers US (Delaware), EU (GDPR), UK, and DACH (German law) jurisdictions with clause libraries for each.

This is not a substitute for legal counsel. Use these templates as strong starting points. Review with an attorney for engagements over $50K or involving complex IP, equity, or regulatory requirements.

Core Capabilities

Fixed-price and hourly development contracts
Monthly consulting retainer agreements
Project proposals with timeline and budget breakdown
Statements of Work (SOW) with deliverables matrix and acceptance criteria
NDAs (mutual and one-way)
Master Service Agreements (MSA) with SOW attachment framework
SaaS partnership agreements (reseller, referral, white-label, integration)
GDPR Data Processing Addenda (Art. 28) for EU/DACH
Jurisdiction-specific clause library (US, EU, UK, DACH)
Change order and scope management clauses

Workflow

Step 1: Requirements Gathering

Gather before drafting:

Question	Why It Matters
Document type?	Contract, proposal, SOW, NDA, MSA
Jurisdiction?	US-Delaware, EU, UK, DACH
Engagement model?	Fixed-price, hourly, retainer, revenue-share
Parties?	Legal names, roles, registered addresses
Scope summary?	1-3 sentences describing the work
Total value or rate?	Drives payment terms and liability caps
Timeline?	Start date, end date or duration, milestones
Special requirements?	IP assignment, white-label, subcontractors, non-compete
Personal data involved?	Triggers GDPR DPA requirement in EU/DACH

Step 2: Template Selection

Document Type	Engagement Model	Template
Dev contract	Fixed-price	Template A: Fixed-Price Development
Dev contract	Hourly/Retainer	Template B: Consulting Retainer
Partnership	Revenue-share	Template C: SaaS Partnership
NDA	Mutual	Template NDA-M
NDA	One-way (discloser/recipient)	Template NDA-OW
SOW	Any	Template SOW (attaches to MSA or standalone)
Proposal	Any	Template P: Project Proposal

Step 3: Generate & Fill

Fill all [BRACKETED] placeholders. Flag missing information as [REQUIRED - description]. Never leave blanks -- an incomplete contract is more dangerous than no contract.

Step 4: Review Checklist

Before sending any generated document:

Clause Library

Payment Terms

Model	Standard Terms	Risk Notes
Fixed-price	50% upfront, 25% at beta, 25% at acceptance	Best for defined scope
Hourly	Net-30, monthly invoicing	Requires time tracking
Retainer	Monthly prepaid, 1st of month	Include overflow rate
Milestone	Per-milestone invoicing	Define milestones precisely
Revenue-share	Net-30 after month close, minimum threshold	Requires audit rights

Late payment: 1.5% per month (US standard), up to statutory maximum in EU/DACH.

Intellectual Property

Jurisdiction	Default IP Ownership	Key Requirement
US (Delaware)	Work-for-hire doctrine	Must be in writing, 9 qualifying categories
EU	Author retains moral rights	Separate written assignment needed
UK	Employer owns (if employee)	Contractor: explicit assignment required
DACH (Germany)	Author retains Urheberrecht permanently	Must transfer Nutzungsrechte (usage rights) explicitly

Pre-existing IP: Always carve out pre-existing tools, libraries, and frameworks. Grant client a perpetual, royalty-free license to use pre-existing IP as embedded in deliverables.

Portfolio rights: Developer retains right to display work in portfolio unless client requests confidentiality in writing within 30 days.

Liability

Risk Level	Cap	When to Use
Standard	1x total fees paid	Most projects
High-risk	3x total fees paid	Critical infrastructure, regulated industries
Uncapped (mutual)	No cap, mutual indemnification	Enterprise partnerships

Always exclude: Indirect, incidental, and consequential damages (both parties).

Termination

Type	Notice Period	Financial Treatment
For cause	14-day cure period	Pay for work completed
For convenience (client)	30 days written notice	Pay for work completed + 10-20% of remaining value
For convenience (either)	30-60 days	Pay for work completed
Immediate (material breach uncured)	7 days post-notice	Pro-rata payment

Confidentiality

Standard term: 3 years post-termination
Trade secrets: Perpetual (as long as information remains a trade secret)
Return/destruction: All confidential materials returned or certified destroyed within 30 days of termination
Exceptions: Publicly known, independently developed, received from third party, required by law

Dispute Resolution

Jurisdiction	Recommended Forum	Rules
US	Binding arbitration	AAA Commercial Rules, Delaware venue
EU	ICC arbitration or local courts	ICC Rules, venue in capital of governing law
UK	LCIA arbitration, London	LCIA Rules, English law
DACH	DIS arbitration or Landgericht	DIS Rules, German law

Jurisdiction-Specific Requirements

US (Delaware)

Governing law: State of Delaware (most business-friendly)
Work-for-hire doctrine applies (Copyright Act 101)
Non-compete: Enforceable with reasonable scope/duration/geography
Electronic signatures: Valid under ESIGN Act and UETA

EU (GDPR)

Data Processing Addendum required if handling personal data
IP assignment may require separate written deed in some member states
Consumer protection laws may override contract terms for B2C
Right to withdraw within 14 days for distance contracts (B2C)

UK (Post-Brexit)

Governed by English law (most common choice)
IP: Patents Act 1977, CDPA 1988
UK GDPR (post-Brexit equivalent) applies for data processing
Electronic signatures: Valid under Electronic Communications Act 2000

DACH (Germany / Austria / Switzerland)

BGB (Buergerliches Gesetzbuch) governs contracts
Schriftform (written form) required for certain clauses (para 126 BGB)
Author always retains moral rights (Urheberpersoernlichkeitsrecht) -- cannot be transferred
Must explicitly transfer Nutzungsrechte (usage rights) with scope and duration
Non-competes: Maximum 2 years, compensation required (para 74 HGB)
DSGVO (German GDPR implementation) mandatory for personal data
Kuendigungsfristen: Statutory notice periods apply and cannot be shortened below minimum

GDPR Data Processing Addendum (Template Block)

Required for any EU/DACH engagement involving personal data:

## DATA PROCESSING ADDENDUM (Art. 28 GDPR/DSGVO)

Controller: [CLIENT LEGAL NAME]
Processor: [SERVICE PROVIDER LEGAL NAME]

### Processing Scope
Processor processes personal data solely to perform services under the Agreement.

### Categories of Data Subjects
[End users / Employees / Customers of Controller]

### Categories of Personal Data
[Names, email addresses, usage data, IP addresses, payment information]

### Processing Duration
Term of the Agreement. Deletion within [30] days of termination.

### Processor Obligations
1. Process only on Controller's documented instructions
2. Ensure authorized persons committed to confidentiality
3. Implement Art. 32 technical and organizational measures
4. Assist with data subject rights requests within [10] business days
5. Notify Controller of personal data breach within [72] hours
6. No sub-processors without prior written consent
7. Delete or return all personal data upon termination
8. Make available information to demonstrate compliance

### Current Sub-Processors
| Sub-Processor | Location | Purpose |
|--------------|----------|---------|
| [AWS/GCP/Azure] | [Region] | Cloud infrastructure |
| [Stripe] | [US/EU] | Payment processing |

### Cross-Border Transfers
Transfers outside EEA: [ ] Standard Contractual Clauses [ ] Adequacy Decision [ ] BCRs

Project Proposal Template (Template P)

# PROJECT PROPOSAL

**Prepared for:** [Client Name]
**Prepared by:** [Your Name / Company]
**Date:** [Date]
**Valid until:** [Date + 30 days]

---

## Executive Summary
[2-3 sentences: what you will build, the business problem it solves, and the expected outcome]

## Understanding of Requirements
[Demonstrate you understand the client's problem. Reference their specific situation, not generic boilerplate]

## Proposed Solution
[Technical approach, architecture overview, technology choices with rationale]

## Scope of Work

### In Scope
- [Deliverable 1: specific description]
- [Deliverable 2: specific description]
- [Deliverable 3: specific description]

### Out of Scope
- [Explicitly list what is NOT included -- prevents scope creep]

### Assumptions
- [Client provides X by Y date]
- [Access to Z system will be available]

## Timeline

| Phase | Deliverables | Duration | Dates |
|-------|-------------|----------|-------|
| Discovery | Requirements document, architecture plan | 1 week | [Dates] |
| Development | Core features, API integration | 4 weeks | [Dates] |
| Testing | QA, UAT, bug fixes | 1 week | [Dates] |
| Launch | Deployment, monitoring, handoff | 1 week | [Dates] |

## Investment

| Item | Cost |
|------|------|
| Discovery & Planning | [Amount] |
| Development | [Amount] |
| Testing & QA | [Amount] |
| Project Management | [Amount] |
| **Total** | **[Amount]** |

### Payment Schedule
- 50% upon contract signing
- 25% at beta delivery
- 25% upon final acceptance

## Why Us
[2-3 concrete differentiators. Reference relevant experience, not just claims]

## Next Steps
1. Review and approve this proposal
2. Sign agreement (attached)
3. Kick-off meeting within [5] business days

Document Conversion

# Markdown to DOCX (basic)
pandoc contract.md -o contract.docx --reference-doc=template.docx

# With numbered sections (legal style)
pandoc contract.md -o contract.docx --number-sections -V fontsize=11pt

# Markdown to PDF (via LaTeX)
pandoc contract.md -o contract.pdf -V geometry:margin=1in -V fontsize=11pt

# Batch convert all contracts
for f in contracts/*.md; do
  pandoc "$f" -o "${f%.md}.docx" --reference-doc=template.docx
done

Common Pitfalls

Pitfall	Consequence	Prevention
Missing IP assignment language	Unclear ownership, disputes	Always include explicit IP clause per jurisdiction
Vague acceptance criteria	Endless revision cycles	Define "accepted" = written sign-off within X days
No change order process	Scope creep on fixed-price	Include change order clause with pricing mechanism
Jurisdiction mismatch	Unenforceable clauses	Match governing law to where parties operate
Missing liability cap	Unlimited exposure	Always cap liability at 1-3x contract value
Oral amendments	Unenforceable modifications	Require written amendments signed by both parties
No DPA for EU data	GDPR violation, up to 4% global revenue fine	Always include DPA when processing EU personal data
Missing force majeure	No protection against unforeseeable events	Include for engagements over 3 months

Best Practices

Use milestone payments over net-30 for projects over $10K -- reduces cash flow risk for both parties
Always include a change order clause in fixed-price contracts
For DACH: include Schriftformklausel (written form clause) explicitly
Define response time SLAs in retainer agreements (e.g., 4h urgent / 24h normal)
Keep templates in version control; review annually as laws change
For NDAs: always specify return/destruction of confidential materials on termination
Include a survival clause -- specify which clauses survive termination (confidentiality, IP, liability)
For EU/DACH: check if consumer protection laws apply (B2C engagements have additional requirements)

Related Skills

Skill	Use When
ceo-advisor	Strategic decisions about partnerships and business models
cfo-advisor	Financial terms, pricing strategy, revenue recognition
launch-strategy	Contract timing around product launches

Tool Reference

1. contract_clause_checker.py

Purpose: Validate a contract document (as structured JSON) against required clauses for a given jurisdiction and engagement type.

python scripts/contract_clause_checker.py contract.json --jurisdiction us-delaware
python scripts/contract_clause_checker.py contract.json --jurisdiction eu --json

Flag	Required	Description
`contract.json`	Yes	JSON file with contract clauses and metadata
`--jurisdiction`	No	Jurisdiction to check against: us-delaware, eu, uk, dach (default: us-delaware)
`--type`	No	Contract type: fixed-price, hourly, retainer, nda, msa (default: fixed-price)
`--json`	No	Output results as JSON

2. proposal_cost_estimator.py

Purpose: Generate a project cost estimate with phase breakdown, payment schedule, and margin analysis.

python scripts/proposal_cost_estimator.py --hourly-rate 150 --hours 200 --phases 4
python scripts/proposal_cost_estimator.py --hourly-rate 150 --hours 200 --phases 4 --json

Flag	Required	Description
`--hourly-rate`	Yes	Hourly rate in dollars
`--hours`	Yes	Estimated total hours
`--phases`	No	Number of project phases (default: 3)
`--margin`	No	Desired profit margin percentage (default: 20)
`--currency`	No	Currency code (default: USD)
`--json`	No	Output results as JSON

3. contract_comparison_analyzer.py

Purpose: Compare two contract versions and identify differences in key clauses, payment terms, and risk areas.

python scripts/contract_comparison_analyzer.py contract_v1.json contract_v2.json
python scripts/contract_comparison_analyzer.py contract_v1.json contract_v2.json --json

Flag	Required	Description
`contract_v1.json`	Yes	JSON file with first contract version
`contract_v2.json`	Yes	JSON file with second contract version
`--json`	No	Output results as JSON

Troubleshooting

Problem	Likely Cause	Solution
Placeholders left in final document	Rushed filling process	Use contract_clause_checker.py to scan for unfilled [BRACKETED] placeholders before sending
IP clause is unenforceable in EU/DACH	Using US work-for-hire language in EU context	Switch to explicit Nutzungsrechte transfer for DACH; use separate written assignment deed for EU
Client disputes scope after signing	Vague acceptance criteria or missing change order process	Define "accepted" = written sign-off within X business days; include change order clause with pricing mechanism
Payment disputes on hourly contracts	No time tracking requirement or unclear invoicing terms	Specify time tracking tool, invoicing frequency (monthly), and payment terms (net-30) in the contract
GDPR non-compliance penalty risk	Missing DPA for EU/DACH engagements involving personal data	Always include Art. 28 DPA when processing EU personal data; use the template block in this skill
Contract fails legal review	Jurisdiction mismatch or missing mandatory clauses	Run contract_clause_checker.py against the target jurisdiction before legal review

Success Criteria

All [BRACKETED] placeholders filled before document delivery
Correct jurisdiction selected and consistent throughout (verified by contract_clause_checker.py)
Payment terms match engagement model with clear invoicing cadence
IP clause matches jurisdiction requirements (work-for-hire for US, Nutzungsrechte for DACH)
Liability cap set at 1-3x contract value with consequential damages excluded
DPA included for all EU/DACH engagements involving personal data
Change order process defined for all fixed-price contracts

Scope & Limitations

In scope: Contract templates, proposal generation, clause libraries, jurisdiction-specific compliance, document comparison, cost estimation
Out of scope: Legal advice, contract negotiation strategy, litigation support, regulatory filings
Not legal counsel: These templates are starting points; review with an attorney for engagements over $50K or involving complex IP, equity, or regulatory requirements
Jurisdiction coverage: US (Delaware), EU (general), UK, DACH (Germany/Austria/Switzerland); other jurisdictions may require additional legal review
Currency: Cost estimator defaults to USD; adjust for local currency in international engagements

Integration Points

ceo-advisor -- Strategic decisions about partnership structures and business models that drive contract type selection
cfo-advisor -- Financial terms, revenue recognition, and pricing strategy that inform payment schedule and margin targets
customer-success-manager -- SOW and MSA structures for customer engagements; renewal terms feed into CS workflows
pricing-strategy -- When proposal pricing needs strategic positioning against competitors or market rates
revenue-operations -- Contract values and payment schedules feed into pipeline forecasting and revenue recognition

When it activates

Automatically, when a task matches. Use when starting client engagements, writing proposals, drafting partnership agreements, or needing GDPR-compliant data processing addenda.

About this skill

Automatic

Legal & Contracts pack

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v5 — 10/8/2026

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IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

thomasmoreai / legal-skills-open

cross-jurisdiction/contracts/skills/contract-and-proposal-writer-borghei/SKILL.md

View on GitHub ↗

License MITImported 8/2/2026Version v1Bundled 3 files · scripts

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What it changes

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Use this skill

Contract & Proposal Writer

Overview

Core Capabilities

Workflow

Step 1: Requirements Gathering

Step 2: Template Selection

Step 3: Generate & Fill

Step 4: Review Checklist

Clause Library

Payment Terms

Intellectual Property

Liability

Termination

Confidentiality

Dispute Resolution

Jurisdiction-Specific Requirements

US (Delaware)

EU (GDPR)

UK (Post-Brexit)

DACH (Germany / Austria / Switzerland)

GDPR Data Processing Addendum (Template Block)

Project Proposal Template (Template P)

Document Conversion

Common Pitfalls

Best Practices

Related Skills

Tool Reference

1. contract_clause_checker.py

2. proposal_cost_estimator.py

3. contract_comparison_analyzer.py

Troubleshooting

Success Criteria

Scope & Limitations

Integration Points

When it activates

SkillSafety

Source

Other skills for the same job

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