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Load all methodology notes · agenticnotetaking | DecimalAI

researchby agenticnotetaking

Load all methodology notes

agenticnotetaking/ask

Source agenticnotetaking/arscontexta ↗License MIT

Query the bundled research knowledge graph for methodology guidance. Routes questions through a 3-tier knowledge base — WHY (research claims), HOW (guidance docs), WHAT IT LOOKS LIKE (domain examples) — plus structured reference documents. Returns research-backed answers grounded in specific claims with practical application to the user's system.

NewMaintained

Automatic

Knowledge Management pack

Last verified 8/12/2026

What it changes

3 of 23 test cases passed with the skill.

Pass-rate lift: —
Tokens: +266%
Agent turns: 0%
Response time: +1%

Model gemini-3.6-flashMeasured 8/12/2026v13 of 23 cases passed with skill · 3 comparable

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

Lift withheld: 3 comparable cases; this report requires 8.

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/agenticnotetaking-ask/SKILL.md https://app.decimal.ai/s/agenticnotetaking-ask/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add agenticnotetaking-ask, 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/agenticnotetaking-ask/ and pins it in .decimal/skills.lock

decimalai skills add agenticnotetaking-ask

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

curl -fsSL --create-dirs -o .claude/skills/agenticnotetaking-ask/SKILL.md https://app.decimal.ai/s/agenticnotetaking-ask/SKILL.md

Raw file: /s/agenticnotetaking-ask/SKILL.md ↗ · machine-readable summary at /s/agenticnotetaking-ask.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 2

Prompt

When reading 5 specific claim IDs retrieved from a search query across the knowledge graph, which MCP tool command should be called to retrieve all 5 documents in a single call?

What was checked, without and with the skill
Checked	Without skill	With skill
Specifies using mcp__qmd__multi_get for batch reading multiple document IDs.	Missed	Passed

case-18 · gemini-3.6-flash · 8/12/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md382 linessingle file

EXECUTE NOW

Question: $ARGUMENTS

If no question provided, ask the user what they want to know.

Execute these steps:

Classify the question — determine which knowledge base tier(s) to consult (see Query Classification below)
Search the knowledge base — route to appropriate tiers based on classification
Read relevant claims and docs — load 3-7 most relevant sources fully (use mcp__qmd__multi_get when reading multiple IDs)
Check user context — read ops/derivation.md if the question involves their specific system
Synthesize an answer — weave claims into a coherent, opinionated argument
Cite sources — reference specific claims and documents so the user can explore further

START NOW. Reference below explains routing and synthesis methodology.

The Three-Tier Knowledge Base

The plugin's knowledge base has three distinct parts, each serving a different function. Effective answers often draw from multiple tiers.

Tier 1: Research Graph (WHY)

Location: ${CLAUDE_PLUGIN_ROOT}/methodology/ — filter by kind: research Content: 213 interconnected research claims grounded in cognitive science, knowledge system theory, and agent cognition research. Use for: Questions about principles, trade-offs, why things work, theoretical foundations.

What it contains:

Claims about how knowledge systems work (human and agent)
Cognitive science foundations (working memory, attention, retrieval)
Methodology comparisons (Zettelkasten vs PARA, atomic vs compound)
Design dimensions (trade-off spectrums with poles and decision factors)
Failure modes and anti-patterns
Agent-specific constraints (context windows, session boundaries)

Search strategy: Use mcp__qmd__deep_search (highest quality, LLM-reranked) for conceptual questions. Use mcp__qmd__vector_search for semantic exploration. Use mcp__qmd__search for known terminology. All searches use the methodology collection.

Tier 2: Guidance Docs (HOW)

Track record

Benchmark

3 / 23

test cases passed with the skill

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 — 8/3/2026

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

agenticnotetaking / arscontexta

skills/ask/SKILL.md

View on GitHub ↗

License MITImported 8/3/2026Version v1

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