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AD feishu-task-management

Manage Feishu tasks through a local Python toolkit that always has app credentials and can optionally act as a user for task APIs when OAuth user tokens are available. Use when Codex needs to create, inspect, update, complete, reopen, delete, or change task members in Feishu Task, especially when member names must be resolved through a locally synced member table and alias mapping instead of ad hoc contact lookups.

ClawHub Agent Skills author: @_@ v0.0.1 MIT-0 26 files body ≈ 1 365 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 48/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, consistency

IntegrationSoftware developmentInfrastructuretype 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%
98
Quality 40%
84
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-high-entropy-token toolkit/config/runtime.json:3
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "app_secret": "xQXr…GWj",
      quoted
    • low Obfuscation obf-base64-blob toolkit/config/runtime.json:8
      Long base64-looking blob (quoted — discussed, not commanded)
      "user_access_token": "eyJh…xNz
      quoted

    Files scanned: 26. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 48/100

    • 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
    • 30Running it twice. 10 mutating operations with no state check
    • 40Consistency. Frontmatter name (feishu-task-management) differs from the folder (feishu-task-management-skill)
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Failures and branches. 2 branches
    • 100Steps. 57 steps
    • 100Execution cost. Instruction body is 1365 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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 418: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 57 items
    • +4Reference files are cited in the instructions (4 of 4)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: suspicious
    The skill does what it claims, but it ships with Feishu credentials, a user token, and cached member data that should not be bundled in a public installable skill.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026