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BD heartbeat-manager

Agent 心跳管理系统：自动检查任务状态、智能超时分析、日报/周报、健康度评分。与 OpenClaw 心跳同步运行。

ClawHub Agent Skills author: Rongze Gao v1.1.0 24 files body ≈ 1 396 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

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

IntegrationGmailSoftware 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
B
83/100
safety, quality, tests
Safety 60%
97
Quality 40%
62
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

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 · 3

✓ No critical or high findings

Medium and low: 3
  • low Exfiltration read-dotenv _meta.json:60
    Reads a .env file (quoted — discussed, not commanded)
    "cp config/.env.example config/.env",
    quoted
  • low Exfiltration read-dotenv SKILL.md:57
    Reads a .env file
    cp config/.env.example config/.env
  • low Exfiltration read-dotenv tools/mail.py:59
    Reads a .env file (quoted — discussed, not commanded)
    "  1. cp config/.env.example config/.env\n"
    quoted

Files scanned: 24. 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. 6 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, git) that frontmatter does not declare
  • 100Steps. 31 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1396 tokens
  • 100Progress reporting. Reports progress

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 59: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -5TODO / placeholder text left in the skill
  • -216 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 31 items
  • +4Has examples (17 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.

External checks

ClawHub: clean
The skill's code, instructions, and optional network/credential usage are consistent with a heartbeat/monitoring manager; nothing in the bundle indicates intentional misdirection or hidden exfiltration, but the user must consciously configure and protect optional credentials and be cautious before enabling git push.
LLM: benign (high) · VirusTotal: benign · 26 Feb 2026