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AF research-assistant

Read Bear notes tagged "待整理", extract topic keywords, search for relevant GIFs via gifgrep, insert them into the note, and remove the tag. Use when the user wants to auto-illustrate or finalize research notes from Bear.

ClawHub Agent Skills author: terrycarter1985 v0.1.0 MIT-0 3 files · 1 script body ≈ 373 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 47/100 · Will not run — References files that are not bundled: GIF_URL

ReferenceInfrastructuretype 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
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
F
47/100
Will not run
References files that are not bundled: GIF_URL
Tools and files w 18
0
Result and completion w 14
0
Progress reporting w 2
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: GIF_URL

Process rating: all ten parameters 47/100

Will not run. References files that are not bundled: GIF_URL
  • 0Tools and files. 1 referenced file(s) missing: GIF_URL
  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (research-assistant) differs from the folder (research-assistant-bear)
  • 55Failures and branches. 1 branches
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 10 steps
  • 100Execution cost. Instruction body is 373 tokens

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
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 219: enough signal without eating the budget
  • +4Structure: 4 headings
  • +3Step-by-step instructions: 10 items
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This skill does what it says: it uses your Bear token to batch-edit tagged Bear notes by adding GIF links and removing the workflow tag.
LLM: benign (high) · VirusTotal: · 29 May 2026