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AF zettel-brainstormer

Build structured brainstorming notes from a seed zettel by retrieving linked notes, preprocessing each note with subagents for relevance extraction, drafting with cited evidence, and publishing a natural blog-style post with a final References section. Use when asked to expand, research, synthesize, or publish from local Obsidian/Zettelkasten notes.

ClawHub Agent Skills author: Xiaoyu Kevin Hu v1.1.2 MIT-0 22 files body ≈ 1 083 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 41/100 · Will not run — References files that are not bundled: scripts/search.py

GeneratorObsidianInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
F
41/100
Will not run
References files that are not bundled: scripts/search.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 20. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/search.py

Process rating: all ten parameters 41/100

Will not run. References files that are not bundled: scripts/search.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/search.py
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 60Failures and branches. 2 branches
  • 100Steps. 54 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1083 tokens
  • 100Running it twice. Mutating operations check current state
  • high The skill tells the model to perform an irreversible action with no human approval

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 351: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 54 items
  • +4Has examples (3 code blocks)
  • +3All 5 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: clean
This skill is a disclosed local-note brainstorming workflow that reads configured Obsidian/Zettelkasten notes, creates temporary draft artifacts, and does not show hidden exfiltration, destructive behavior, or unsafe persistence.
LLM: benign (high) · VirusTotal: benign · 28 May 2026