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AC dingtalk-api

调用钉钉开放平台API，支持用户搜索/详情/查询、部门管理（搜索/详情/子部门/用户列表/父部门）、机器人单聊消息发送、群聊消息发送、群内机器人列表查询、离职记录查询。Use when needing to search DingTalk users or departments, get user/department details, send robot messages, list group bots, or query resigned employees.

ClawHub Agent Skills author: ogenes v1.4.0 38 files body ≈ 2 576 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

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

IntegrationInfrastructuretype 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
90/100
safety, quality, tests
Safety 60%
95
Quality 40%
82
Run on models
none yet
Process rating
C
51/100
Has gaps
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

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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token package-lock.json:70
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…eSU+cNQNOxW+SFmg…2LB+KNRu…2X3/keq9h6++S9jcV5g==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:94
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…0Vh+glXKun2/9Upa…hDF/kxDmDJoNYiTw==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:116
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…CUc+5vKT…2QQ==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:132
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…BOB+GCvG…Q4w/+Yww==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:216
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…xCA+ORZv…wO5/ywWF…Tag==",
      detector

    Files scanned: 38. 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
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 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. 3 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 6 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2576 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
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +3Description length 237: enough signal without eating the budget
    • +4Structure: 35 headings
    • +3Step-by-step instructions: 6 items
    • +4Has examples (62 code blocks)
    • +3All 30 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    This DingTalk API skill appears legitimate, but it can read employee/workflow data and change approval workflows with app credentials, so it needs careful review before use.
    LLM: suspicious (high) · VirusTotal: benign · 28 May 2026