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BF content-collector

Automatically collect and archive content from shared links in group chats. When a user shares a link (WeChat articles, Feishu docs, web pages, etc.) in any group chat and asks to archive/collect/save it, this skill triggers to fetch the content, create a Feishu document, and update the knowledge base table. Use when: (1) User shares a link and asks to "收录/转存/保存" content, (2) Need to archive web content to Feishu docs, (3) Building a personal knowledge base from shared links, (4) Organizing learning materials from various sources.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 2 files body ≈ 4 686 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Automatically collect and archive content from shared links in group chats.

As a process F 47/100 · Will not run — References files that are not bundled: {new_doc_url}, url, {image_key}

ProcedureWordWriting and documentsPersonal productivitytype 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
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
F
47/100
Will not run
References files that are not bundled: {new_doc_url}, url, {image_key}
Tools and files w 18
0
Inputs and preconditions w 11
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Automatically collect and archive content from shared links in gro… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning missing-ref reference to a missing file: {new_doc_url}
  • warning missing-ref reference to a missing file: url
  • warning missing-ref reference to a missing file: {image_key}
  • warning missing-ref reference to a missing file: {img_url}
  • warning missing-ref reference to a missing file: {original_url}

Process rating: all ten parameters 47/100

Will not run. References files that are not bundled: {new_doc_url}, url, {image_key}
  • 0Tools and files. 5 referenced file(s) missing: {new_doc_url}, url, {image_key}
  • 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
  • 40Consistency. Frontmatter name (content-collector) differs from the folder (content-collector-skill)
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 4686 tokens
  • 100Steps. 71 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Running it twice. Mutating operations check current state
  • low 16 top-level sections: this looks like several domains in one skill

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)
  • -249 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 536: enough signal without eating the budget
  • +4Structure: 45 headings
  • +3Step-by-step instructions: 71 items
  • +3Output format is stated explicitly
  • +4Has examples (23 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.