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Data Story Outliner · dicklesworthstone | DecimalAI

Registry skillby dicklesworthstone

Data Story Outliner

dicklesworthstone/data-story-outliner

Source dicklesworthstone/pi_agent_rust ↗License NOASSERTION

Process data story outliner operations. Auto-activating skill for Data Analytics.

NewMaintained

Automatic

Data Analyst pack

Last verified 8/30/2026

What it changes

Passed 10 of 23 test cases with the skill, and 13 of 23 without it.

Without skill57%

With skill43%

Checks it passed that the model alone missed

The outline compares CAC payback periods across segments.
The outline quantifies working capital tied up in low-velocity SKUs.
The outline categorizes SKU recommendations by turnover velocity tier.

and 1 more in the full report

3 fixed10 passed either way6 still failing4 broke

Pass-rate lift: -14 pp
Tokens: +26%
Agent turns: 0%
Response time: +5%

Model gemini-3.6-flashMeasured 8/30/2026v113 of 23 cases passed with skill

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/dicklesworthstone-data-story-outliner/SKILL.md https://app.decimal.ai/s/dicklesworthstone-data-story-outliner/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add dicklesworthstone-data-story-outliner, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/dicklesworthstone-data-story-outliner/ and pins it in .decimal/skills.lock

decimalai skills add dicklesworthstone-data-story-outliner

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/dicklesworthstone-data-story-outliner/SKILL.md https://app.decimal.ai/s/dicklesworthstone-data-story-outliner/SKILL.md

Raw file: /s/dicklesworthstone-data-story-outliner/SKILL.md ↗ · machine-readable summary at /s/dicklesworthstone-data-story-outliner.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 3

Prompt

Our multi-touch attribution model shows paid search driving 40% of conversions, while organic content drives 35%. Marketing leadership wants a data story outline to justify reallocating $500k from display ads to search. How should we structure the ROI story arc?

What was checked, without and with the skill
Checked	Without skill	With skill
The outline establishes baseline channel performance before proposing budget shifts.	Passed	Passed
The outline details projected incremental conversion yield for the proposed budget reallocation.	Missed	Passed

case-10 · gemini-3.6-flash · 8/30/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md60 linessingle file

Data Story Outliner

Overview

This skill provides automated assistance for data story outliner tasks within the Data Analytics domain.

When to Use

This skill activates automatically when you:

Mention "data story outliner" in your request
Ask about data story outliner patterns or best practices
Need help with data analytics skills covering sql queries, data visualization, statistical analysis, and business intelligence.

Instructions

Provides step-by-step guidance for data story outliner
Follows industry best practices and patterns
Generates production-ready code and configurations
Validates outputs against common standards

Examples

Example: Basic Usage Request: "Help me with data story outliner" Result: Provides step-by-step guidance and generates appropriate configurations

Prerequisites

Relevant development environment configured
Access to necessary tools and services
Basic understanding of data analytics concepts

Output

Generated configurations and code
Best practice recommendations
Validation results

Track record

Benchmark

10 / 23

test cases passed, vs 13 / 23 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/10/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

dicklesworthstone / pi_agent_rust

tests/ext_conformance/artifacts/plugins-community/skills/12-data-analytics/data-story-outliner/SKILL.md

View on GitHub ↗

License MITImported 8/10/2026Version v1

More skills from the same source and nearby in the registry, with their headline benchmark lift.

Ready to supercharge your AI agents?

See it in action

What's inside

Data Story Outliner

Overview

When to Use

Instructions

Examples

Prerequisites

Output

Track record

Benchmark

Adoption

SkillSafety

Source

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