SKILLEMALL.ai

AC feishu-doc-editor

Feishu document creation and editing operations using OpenAPI. Activate when user needs to create, edit, or read Feishu documents programmatically.

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files body ≈ 854 tokens Open the sourcegithub.com analyzed 2 d ago

Feishu document creation and editing operations using OpenAPI.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

GeneratorWordWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
97
Quality 40%
80
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • low Exfiltration exfil-secret-in-url references/api-guide.md:409
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      RESONSE=$(curl -s "https://open.feishu.cn/open-apis/docx/v1/documents/DOC_ID/blocks/DOC_ID/children?page_size=100&page_token=…" \
      placeholder
    • low Exfiltration net-credential-use references/api-guide.md:409
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
      RESONSE=$(curl -s "https://open.feishu.cn/open-apis/docx/v1/documents/DOC_ID/blocks/DOC_ID/children?page_size=100&page_token=…" \
      vendor-host
    • low Secrets in code secret-labelled-token references/common-errors.md:543
      Labelled token / key literal (vendor format unknown — verify it is not a live credential) (placeholder value)
      APP_SECRET="abcd…456"
      placeholder

    Files scanned: 4. 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 51/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 8 mutating operations with no state check
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 16 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 854 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
    • -43 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +3Description length 147: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 16 items
    • +4Has examples (6 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.