Bug Receipt logo

Bug Receipt

OrganizationPopular
github
bug-receipt

Close defects and incidents with a BUG RECEIPT and VERIFIED, PARTIAL, or BLOCKED status after diagnosis, repair, or recovery.

Overview

Publishergithub
Repositoryawesome-copilot
Skill namebug-receipt
Stars
39.6K
Forks
5K
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by github on GitHub. Read the source before you install it.

Installation

Install the Bug Receipt AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/github/awesome-copilot/tree/main/skills/bug-receipt
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/github/awesome-copilot.git /tmp/awesome-copilot
mkdir -p .claude/skills
cp -r /tmp/awesome-copilot/skills/bug-receipt .claude/skills/bug-receipt
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bug Receipt in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Bug Receipt on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Bug Receipt is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Bug Receipt

Mandatory closeout output

For every bug or incident closeout decision, return the complete receipt below as the entire user-facing result, even when the user requests a concise reply or does not name this format. Concision shortens field values; it never removes or renames a row. Do not replace the receipt with prose.

text
BUG RECEIPT · VERIFIED | PARTIAL | BLOCKED

Problem    <observed defect and intended behavior>
Baseline   <failing interaction or command and decisive result; or not run>
Root cause <proven mechanism; or unproven hypothesis>
Change     <responsible change; or none>
Proof      <supplied or executed check: result; include every decisive layer>
Gaps       <none; or exact missing proof and single next experiment/package>
Source     executed now | supplied | mixed

Use not run, unproven, or none explicitly. Never omit a row to make the receipt look complete.

Establish the evidence boundary

Before editing, record the observed problem, intended behavior, strongest direct check, and evidence source: executed now, supplied, or mixed. Never imply that supplied evidence was executed in the current run.

Keep evidence privacy-minimal. Redact credentials, tokens, cookies, personal data, private URLs, and sensitive payloads; preserve only the identifiers and excerpts needed to reproduce or correlate the failure.

Reproduce the failure with the narrowest safe check when possible. If reproduction is unavailable, preserve the evidence obtained and cap the result at PARTIAL or BLOCKED.

Trace and repair

  1. Follow the live owner path from input to symptom.
  2. Separate observed facts, bounded inferences, and gaps.
  3. Require a concrete location or runtime transition before naming root cause.
  4. Make the smallest responsible change; avoid unrelated cleanup, retries, silent fallbacks, and fixture-specific exceptions.

Do not convert a plausible patch, stale log, source read, or passing build into proof of the user-visible behavior.

Close the proof loop

Run only checks required by the affected contract:

  • original reproduction or direct acceptance check;
  • nearest negative or regression check;
  • affected build or integration gate;
  • real UI, API, persistence, concurrency, or runtime path when the claim crosses that boundary.

Use these decisive boundaries:

SurfaceRequired direct proof
Logic or failing testOriginal failing input or focused test now passes
UI behaviorReal interaction plus relevant console and network observation
API or integrationRequest, response, and responsible service behavior
PersistenceWrite/read or reload round trip through the real owner path
Race or lifecycleRepeated concurrent trigger; zero-or-one success; affected-row and transaction evidence; final invariant
Cross-system blockerOne sanitized failing request/response with timestamp or request ID, edge and application logs, and identity-provider logs when the trace reaches that owner

Assign status

  • VERIFIED: observed baseline, concrete cause, responsible change, all declared checks passed, no material gap.
  • PARTIAL: useful evidence exists, but a required proof layer is missing or inconclusive.
  • BLOCKED: a specific external condition prevents reproduction, repair, or proof.

For PARTIAL or BLOCKED, name the single minimal experiment or correlated evidence package that closes the decisive gap. Never invent a command, observation, count, location, or result.

For a machine-readable receipt or CI integration, read references/receipt-contract.md and conform to its JSON fields, evidence-source marker, compatibility rule, and status invariants.

When a JSON artifact is requested, start from assets/receipt.template.json, write it to a task-owned path, and validate it with node scripts/validate-receipt.mjs <receipt.json> from this skill directory. Do not commit the generated receipt unless the user requests it.

Source and license

Originally published at https://github.com/lMysticl/bug-receipt under the MIT License.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Bug Receipt AI skill do?

Close defects and incidents with a BUG RECEIPT and VERIFIED, PARTIAL, or BLOCKED status after diagnosis, repair, or recovery.

Why use Bug Receipt on TypingMind?

Because you install it once and use it with any model. Bug Receipt is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Bug Receipt in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/github/awesome-copilot/tree/main/skills/bug-receipt. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Bug Receipt?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Bug Receipt?

As many as you like. As long as a model supports skills, you can use Bug Receipt with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Bug Receipt AI skill free?

Yes. It is published on GitHub by github under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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