Apache Magpie is a framework of agent-assisted workflows for maintaining Apache software projects, including issue triage, pull-request review, contributor mentoring, and security-report handling. Apache maintainers and developers use it to delegate repetitive project work to coding agents while retaining human review. Its catalogue entries are the skills, instructions, plugin, and settings that implement these workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add apache/magpie --skill audit-reportgit clone --depth 1 https://github.com/apache/magpieWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/apache/magpie/audit-report)<a href="https://agentmods.dev/skills/apache/magpie/audit-report"><img src="https://agentmods.dev/badge/skills/apache/magpie/audit-report/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/apache/magpie/audit-report"><img src="https://agentmods.dev/badge/skills/apache/magpie/audit-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00070 | $0.05257 |
| Opus 5.5 | $0.00028 | $0.02103 |
| Sonnet 5.5 | $0.00014 | $0.01051 |
| Haiku 4.5 | $0.00007 | $0.00526 |
Grade A, and why
audit-report scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 397 lines — stays where its author put it; the contents beside it link to each section on GitHub.
release-audit-report
Pre-flight — is this project set up?
Do this first, before anything else in this skill, and do it silently. One command answers it and carries its own rules; there is nothing else to read.
Run the checker with this skill's own frontmatter name: and
surface_hash:, and one --requires for each requires_config: entry:
PYTHONPATH=".apache-magpie-local:$(git rev-parse --git-common-dir)/../.apache-magpie-local:$(git rev-parse --git-common-dir)/apache-magpie" \
python3 -m setup_preflight --skill <name> --hash <surface_hash> [--requires <file>]...
The path finds the checker /magpie-setup:setup config installed in the
personal layer: this checkout's .apache-magpie-local/, the main
checkout's when this is a linked worktree, or the git directory's
apache-magpie/ when Magpie is only installed.
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago Changed · -122 lines 5895a55e1737
- 5d ago Changed · +2 lines a98ea74363ca
- 7d ago Changed 4caf3977be9e
- 9d ago Changed 85db8642d9e4
- 15d ago Changed · -54 lines 81b18382ef8a
- 16d ago Changed · -12 lines e9d356674054
- 17d ago Changed · +1 lines 1c612a84b790
- 21d ago Changed · -11 lines 1291bdf9a2f6
- 22d ago Changed · +1 lines 91b9fc09bfb8
- 24d ago First seen · 592 lines · 70 tokens per session scan A 5dbc6b33ffcc
audit-report is a skill published in the GitHub repository apache/magpie (120 stars, last pushed today), licensed Apache-2.0. It adds 70 tokens to every session and 5,257 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-14.
Other skills, from other repositories
batch
Research and plan a large-scale change, then execute it in parallel across 5–30 isolated worktree agents that each open a PR.
team-release
Orchestrate the release team — release-manager, qa-lead, devops-engineer, producer — to execute a release from candidate to deployment.
operating-github-cli
Default GitHub skill for the action agent. Use githubcli for any GitHub request — create/list/view/close issues and PRs, assign, labels, repos, releases, checks, github.com/owner/repo URLs, or gh api. Prefer over shellrun/!gh. Run these with githubcli in the current agent turn.
github
Drive GitHub via the official gh CLI — repos, issues, pull requests, releases, gists, Actions runs, and raw REST through gh api. Use when the user asks to inspect or manage GitHub.
testdino-releases
Use when the user wants to browse, inspect, create, or update releases/milestones in a TestDino project. Covers listreleases, getrelease, createrelease, and updaterelease. Accepts counter-style IDs like MS-12.
create-milestone
Create a GitHub milestone for an upcoming release. Suggests the next version based on the latest release, gathers all merged PRs and closed issues since that release, presents a draft with two tables (Issues and PRs) for user approval, then creates the milestone and assigns all approved items.