Enforce real progress for long-running tasks by separating execution from reporting. Use when users complain that the agent is "saying it's working" without concrete output, when a task is stalling, or when you need a hard proof loop (file changes, commit checks, and blocker alerts) every 15-30 minutes.
Scanned 9/7/2026
Install to Claude Code
npx -y skills add modbender/skill-library-mcp --skill execution-verifier --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: execution-verifier
description: Enforce real progress for long-running tasks by separating execution from reporting. Use when users complain that the agent is "saying it's working" without concrete output, when a task is stalling, or when you need a hard proof loop (file changes, commit checks, and blocker alerts) every 15-30 minutes.
---
# Execution Verifier
Use this skill to prevent fake progress.
## Core policy
- Treat "no artifact change" as "no progress".
- Report only hard evidence: file changes, line deltas, commits, test outputs.
- If no evidence is detected in the time window, report blocker + immediate next action.
## Minimal operating loop (30 min)
1. **Execute** one concrete next action from OPEN_TASKS.
2. **Write artifacts** (target files must change).
3. **Verify** with `scripts/verify_progress.py`.
4. **Report** in strict 3-line format.
## Strict report format
1) 已完成:`<file path + concrete change>`
2) 进行中:`<current actionable step>`
3) 下一步+ETA:`<next step + time>`
If verification fails, replace line 1 with: `本轮无新增(原因:<blocker>)`.
## Verifier command
```bash
python3 skills/execution-verifier/scripts/verify_progress.py \
--project-dir projects/ai-human-co-production \
--status projects/ai-human-co-production/STATUS.md \
--open-tasks projects/ai-human-co-production/OPEN_TASKS.md \
--window-min 30
```
## Closed-loop mode (verify → auto-execute → re-verify)
Use built-in script:
```bash
python3 skills/execution-verifier/scripts/verify_execute_verify.py \
--verify-cmd "python3 skills/execution-verifier/scripts/verify_progress.py --project-dir projects/ai-human-co-production --status projects/ai-human-co-production/STATUS.md --open-tasks projects/ai-human-co-production/OPEN_TASKS.md --window-min 30" \
--execute-cmd "openclaw cron run fc567f18-83fa-426c-8181-71a10f4568b3 --force"
```
Behavior:
- Step A: verify current progress
- Step B: if no progress, auto-trigger executor
- Step C: verify again
- Output JSON includes `before`, `triggered_execute`, `after`
## Cron pattern (recommended)
Use two jobs:
- **Executor job (isolated agentTurn, every 30m):** do real work + write files.
- **Verifier job (main systemEvent, every 30m offset +5m):** run closed-loop script above.
Never run report-only cron without verifier.
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