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BC feishu

Read and write Feishu (飞书) docs, sheets, Base (bitable), Drive files, calendar events, tasks, wiki, and IM messages via the Feishu Open Platform REST API. Use when the user mentions 飞书 / Feishu / Lark, a Feishu document or sheet link, their Feishu calendar, or wants to send a Feishu message.

AceDataCloud/Skills Agent Skills author: AceDataCloud 1 file body ≈ 2 031 tokens Open the sourcegithub.com↗ analyzed 2 h ago

Read and write Feishu (飞书) docs, sheets, Base (bitable), Drive files, calendar events, tasks, wiki, and IM messages via the Feishu Open Platform REST API.

As a process C 56/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, running it twice

GeneratorWordPersonal productivitytype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
99
Quality 40%
86
Run on models
none yet
Process rating
C
56/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Running it twice w 4
30
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Exfiltration net-credential-use SKILL.md:20
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
      $FEISHU_TOKEN`. All endpoints live under `https://open.feishu.cn/open-apis`.
      vendor-host

    Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "connections"
    • note frontmatter-key unknown frontmatter key "allowed_tools"

    Process rating: all ten parameters 56/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 30Running it twice. 10 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 75Steps. 3 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2031 tokens
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (3 tags): a typed call is more reliable

    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)
    • +2Single-language instructions
    • +3Description length 292: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 3 items
    • +3Output format is stated explicitly
    • +4Has examples (18 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.