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Count total notes (excluding MOCs) · agenticnotetaking | DecimalAI

documentationby agenticnotetaking

Count total notes (excluding MOCs)

agenticnotetaking/graph

Source agenticnotetaking/arscontexta ↗License MIT

Interactive knowledge graph analysis. Routes natural language questions to graph scripts, interprets results in domain vocabulary, and suggests concrete actions.

SkillScore46Maintained

Automatic

Knowledge Management pack

Last verified 8/12/2026

What it changes

Passed 6 of 14 test cases with the skill, and 4 of 14 without it.

Without skill27%

With skill46%

Checks it passed that the model alone missed

Classifies graph density above 0.15 as Very dense.
Checks ops/config.yaml for graph threshold limits.
Excludes pairs that already belong to the same Map of Content.

and 6 more in the full report

8 fixed4 passed either way11 still failing3 broke

Pass-rate lift: +19 pp
Tokens: +193%
Agent turns: 0%
Response time: -36%

Model gemini-3.6-flashMeasured 8/12/2026v112 of 26 cases passed with skill · 14 comparable

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

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

decimalai skills add agenticnotetaking-graph

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

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

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

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 8

Prompt

When reporting raw graph metrics, triangle pairs, or isolated clusters, what rule governs how structural findings must be presented to the user?

What was checked, without and with the skill
Checked	Without skill	With skill
Requires accompanying domain context descriptions rather than dumping raw data.	Passed	Passed
Demands actionable next step recommendations for every reported finding.	Missed	Passed

case-23 · 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.md555 linessingle file

Runtime Configuration (Step 0 — before any processing)

Read these files to configure domain-specific behavior:

ops/derivation-manifest.md — vocabulary mapping, platform hints
- Use vocabulary.notes for the notes folder name
- Use vocabulary.note / vocabulary.note_plural for note type references
- Use vocabulary.topic_map / vocabulary.topic_map_plural for MOC references
- Use vocabulary.cmd_reflect for connection-finding command name
- Use vocabulary.cmd_reweave for backward-pass command name
ops/config.yaml — for graph thresholds (MOC size limits, orphan thresholds)

If no derivation file exists, use universal terms (notes, MOCs, etc.).

EXECUTE NOW

Target: $ARGUMENTS

Parse the operation from arguments:

If arguments match a known operation: route to that operation
If arguments are a natural language question: map to the closest operation (see Interactive Mode)
If no arguments: enter interactive mode

START NOW. Route to the appropriate operation.

Philosophy

The graph IS the knowledge. This skill makes it visible.

Individual {vocabulary.note_plural} are valuable, but their connections create compound value. /graph reveals the structural properties of those connections — where the graph is dense, where it is sparse, where it is fragile, and where synthesis opportunities hide.

Every operation produces two things: findings (what the analysis reveals) and actions (what to do about it). Never dump raw data. Always interpret results with {vocabulary.note} descriptions and domain context. Always suggest specific next steps.

Track record

Benchmark

6 / 14

test cases passed, vs 4 / 14 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 — 8/3/2026

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

skill-sources/graph/SKILL.md

View on GitHub ↗

License MITImported 8/3/2026Version v1

Other skills for the same job

Published skills whose descriptions closely match this one, with their headline benchmark lift.

miosa-osa/graph9 graph analysis operations for knowledge networks: triangles (synthesis opportunities), bridges (critical connectors), clusters (isolated subgraphs), hubs (high-degree nodes), siblings (unconnected items sharing topics), forward/backward traversal, orphans, and staleness scan. The analytical lens on your knowledge structure. Triggers on: "graph", "connections", "network analysis", "knowledge map"Close match+43 pp pass-rate lift

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