# Agent Receipt

> Create a compact, evidence-backed proof-of-work receipt for a completed AI agent run. Use when the user wants to summarize what an agent actually built, how long it took, what changed, tests run, interventions, deployment status, or skills used.

- Skill: `getedgehq/agent-receipt` (Agent Skill, multi-file: 9 files)
- Install (CLI): `npx skillmds@latest add getedgehq/agent-receipt`
- Raw SKILL.md: https://api.skillmd.com/api/skills/getedgehq/agent-receipt/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: getedgehq (https://skillmd.com/u/getedgehq)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/getedgehq/agent-receipt

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# Agent Receipt

1. Gather only evidence available in the current run/repo.
2. Never infer a passed test, deployment, duration, or intervention count. Use `unknown` instead.
3. Write a local JSON manifest with: project, agent, duration_minutes, interventions, files_changed, tests_passed, tests_total, verification, deployed, skills_used, and evidence.
4. Run `scripts/receipt.py <manifest> --out <public-result.json>`. The public result contains evidence hashes and counts, never raw evidence values.
5. Run `scripts/render.py <public-result.json> --svg <card.svg> [--png <card.png>]`.
6. Keep the source manifest and raw evidence local unless the user explicitly approves publishing selected evidence.
7. Publishing is a separate external action. Confirm destination and visibility immediately before uploading unless the current request already authorizes it.