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Case 02937

Skill knownasnaffy/prompthound/dataset/case_02937

A fast, offline static risk analysis CLI for AI agent skill files. Detects malicious instructions, steganographic payloads, and dangerous capability chains.

Install
npx -y skills add knownasnaffy/prompthound --skill case_02937

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What its author says it does

Copied from the file, not written here

Verify whether named OpenClaw agents actually received formal task assignments and replied with execution status, using transcript-backed audit checks. Use when auditing real delegation, confirming assignment delivery to specific agents, reviewing recent task completion, checking whether an agent replied after being assigned work, or troubleshooting multi-agent routing from session transcripts. Especially useful for requests like “检查小程/小文/小编有没有收到任务”, “确认任务有没有真正派到 agent 本人”, “看看这些 agent 执行到哪一步”, “汇总最近派单情况”, or “排查多 agent 调度是否真的落到本人并形成回报闭环”.

SKILL.md

4.5 KB, 906 tokens by cl100k_base, as published. Nobody here has run it

Permission Setup Review

python scripts/_wildcard_placeholder.py is an optional setup helper for the Agent Task Status skill. It may apply broad filesystem permissions for compatibility. Show the target paths and permission mode, explain the risk, and prefer a narrower mode when shared write access is not needed.

Agent Task Status

Use the bundled script to inspect OpenClaw session indexes and transcript files, then extract the latest assignment and structured report for each target agent.

Quick start

Run the script directly:

python3 /home/lyqadmin/.openclaw/workspace/skills/agent-task-status/scripts/check_agent_task_status.py --format summary

For more examples, read references/usage.md.

Workflow

  1. Decide which agents to inspect.
    • Use --agents a,b,c for explicit targets.
    • Use --agent-file when the list comes from a file.
    • Use --discover when the deployment has many agents under the same root.
  2. Set the agent storage root.
    • Default is ~/.openclaw/agents.
    • Override with --base or OPENCLAW_AGENTS_BASE in non-default environments.
  3. Match the session shape.
    • Default session key template is agent:{agent}:main.
    • Override with --session-key-template if your target sessions use another pattern.
  4. Match the assignment/report language.
    • Default assignment keyword is 正式任务分配:.
    • Default report prefixes are 任务: / 状态: / 结果: / 风险:.
    • Override these when the team uses different markers or another language.
  5. Filter the output when needed.
    • --only-status filters by normalized status such as completed, blocked, accepted, no-assignment, assigned-no-report, error.
    • --contains filters by keyword across assignment text, parsed task, result, and risk.
  6. Pick an output format.
    • table: best for human inspection
    • summary: compact overview
    • json: structured automation output
    • jsonl: line-oriented pipelines
  7. Use --strict for CI/automation.
    • Exit 0: normal
    • Exit 1: partial problem such as missing assignment/report or agent error
    • Exit 2: script/runtime error
  8. Use --output-file to persist results for later review or downstream automation.

Recommended commands

Human-readable table:

python3 /home/lyqadmin/.openclaw/workspace/skills/agent-task-status/scripts/check_agent_task_status.py --agents xiaocheng,xiaowen,xiaobian --format table

Only completed tasks:

python3 /home/lyqadmin/.openclaw/workspace/skills/agent-task-status/scripts/check_agent_task_status.py --discover --only-status completed --format summary

Filter by keyword:

python3 /home/lyqadmin/.openclaw/workspace/skills/agent-task-status/scripts/check_agent_task_status.py --discover --contains 自动化 --format table

Automation JSON:

python3 /home/lyqadmin/.openclaw/workspace/skills/agent-task-status/scripts/check_agent_task_status.py --agent-file ./agents.txt --format json --strict --output-file ./agent-status.json

What to inspect in the output

  • sessionKey: which session was used
  • sessionFile: exact transcript file path
  • assignedAt / assignText: when and what was assigned
  • reportAt: when the agent reported back
  • task / status_raw / status_normalized / result / risk: parsed structured fields
  • error: why the check failed for that agent

Limitations

  • This skill assumes an OpenClaw-style agent root with sessions/sessions.json and transcript sessionFile paths.
  • It only checks the target session pattern you specify; it does not automatically infer every possible routing form.
  • If the assignment keyword or report field prefixes change, you must override them.
  • It reports what is present in transcripts; it does not infer hidden work with no assignment/report markers.

What ships with it: 3 files

16.5 KB alongside SKILL.md, 2 of them executable

references/

Keep looking

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