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CD feishu-log

飞书日志记录 - 用户主动提供日志内容，智能整理、结构化、层次化后写入飞书文档，不使用固定模板。使用场景：(1) 会议记录，(2) 项目日志，(3) 工作复盘，(4) 重要事件记录

ClawHub Agent Skills author: tonyvics v1.0.1 MIT-0 15 files · 1 script body ≈ 1 972 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

飞书日志记录 - 用户主动提供日志内容，智能整理、结构化、层次化后写入飞书文档，不使用固定模板。使用场景：(1) 会议记录，(2) 项目日志，(3) 工作复盘，(4) 重要事件记录

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationWordSoftware developmenttype 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
C
72/100
safety, quality, tests
Safety 60%
76
Quality 40%
67
Run on models
none yet
Process rating
D
45/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Secrets in code medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 12

✓ No critical or high findings

Medium and low: 12
  • medium Secrets in code secret-labelled-token log-simple.mjs:11
    Labelled token / key literal (vendor format unknown — verify it is not a live credential)
    const APP_SECRET = 'aMRJ…srs';
  • medium Secrets in code secret-labelled-token log-work.mjs:53
    Labelled token / key literal (vendor format unknown — verify it is not a live credential)
    appSecret: "aMRJ…srs",
  • medium Secrets in code secret-labelled-token README.md:137
    Labelled token / key literal (vendor format unknown — verify it is not a live credential)
    const APP_SECRET = "aMRJ…srs";
  • low Secrets in code secret-high-entropy-token config-credentials.js:61
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    app_secret: appSecret.trim() || "aMRJ…srs",
    detector
  • low Secrets in code secret-high-entropy-token log-interactive.mjs:5
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    const appSecret = process.env.FEISHU_APP_SECRET || "aMRJ…srs";
    detector
  • low Exfiltration net-credential-use log-interactive.mjs:133
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    const docUrl = `https://wcnh….cn/docx/${docToken}`;
    vendor-host
  • low Secrets in code secret-high-entropy-token log-simple.mjs:11
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    const APP_SECRET = 'aMRJ…srs';
    detector
  • low Secrets in code secret-high-entropy-token log-work.mjs:53
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    appSecret: "aMRJ…srs",
    detector
  • low Exfiltration net-credential-use log-work.mjs:241
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    const docUrl = `https://wcnh….cn/docx/${docToken}`;
    vendor-host
  • low Secrets in code secret-high-entropy-token log.js:23
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    const APP_SECRET = process.env.FEISHU_APP_SECRET || "aMRJ…srs";
    detector
  • low Exfiltration net-credential-use log.js:158
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    const docUrl = `https://wcnh….cn/docx/${docToken}`;
    vendor-host
  • low Secrets in code secret-high-entropy-token README.md:137
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    const APP_SECRET = "aMRJ…srs";
    detector

Files scanned: 15. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 45/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 7 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 89 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1972 tokens
  • 100Progress reporting. Reports progress
  • low 15 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)
  • +3Description length 90: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -234 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 44 headings
  • +3Step-by-step instructions: 89 items
  • +4Has examples (16 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: suspicious
The skill's code and instructions largely match its stated purpose (writing structured logs to Feishu), but there are several inconsistencies and risky defaults (hard-coded fallback credentials, mismatch between registry metadata and SKILL.md environment requirements, and use of an app-level tenant token with wide drive permissions) that warrant caution before installation.
LLM: suspicious (medium) · 13 Mar 2026