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 model-preparegit 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/model-prepare)<a href="https://agentmods.dev/skills/apache/magpie/model-prepare"><img src="https://agentmods.dev/badge/skills/apache/magpie/model-prepare/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/model-prepare"><img src="https://agentmods.dev/badge/skills/apache/magpie/model-prepare.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 | $0.00066 | $0.04673 |
| Opus 5.5 | $0.00026 | $0.01869 |
| Sonnet 5.5 | $0.00013 | $0.00935 |
| Haiku 4.5 | $0.00007 | $0.00467 |
Grade A, and why
model-prepare scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 375 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security model prepare
Pre-flight — is this project set up?
Do this first, before anything else in this skill, and do it silently. One command answers it and carries its own rules; there is nothing else to read.
Run the checker with this skill's own frontmatter name: and
surface_hash:, and one --requires for each requires_config: entry:
PYTHONPATH=".apache-magpie-local:$(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.
{"verdict": "ok"}→ silent. Continue into the work the user asked for and say nothing about pre-flight. This is the ordinary answer.{"verdict": "action", ...}→ each finding names a section, andrulescarries that section's text. Follow it. Thefactsare the inputs; what to propose, and what may not be done, are in the rules rather than here. Act on a finding only through its rules.- The command did not run at all — no such module, a non-zero exit, no
python3— → never read that as a pass, and do not re-derive the check by hand: it lives in code so that there is one version of it. If the project has no.apache-magpie.lock,.apache-magpie-overrides/, or personal layer (any of the three directories above), nothing has been set up here and there is nothing to reconcile — resolve this skill'srequires_config:entries yourself (first match wins:.apache-magpie-local/<file>, the main checkout's.apache-magpie-local/<file>,<git-common-dir>/apache-magpie/<file>, then.apache-magpie-overrides/<file>), stay silent if they all resolve, and run/magpie-setup:setup configfor this skill if any does not, which also installs the checker. Otherwise the project is set up and its checker is missing or stale: say so, propose/magpie-setup:setup configto install it or/magpie-setup:setup upgradeto refresh it, and carry on with the work.
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.
- 5d ago Changed · +2 lines 9c9befd19bbd
- 9d ago Changed 470b4f65dbfe
- 15d ago Changed · +7 lines 59535451b550
- 22d ago Changed · -6 lines 0058087392a8
- 23d ago Changed · -11 lines · -76 tokens per session 2173ef4a3f92
- 24d ago Changed · +1 lines 3470d4301a9a
- 26d ago Changed · +73 lines e3d70f392ad3
- 27d ago Changed · -3 tokens per session b96c828695ea
- 28d ago Changed · -94 lines 3ac121e281e4
- 1mo ago First seen · 403 lines · 145 tokens per session scan A eef552bcf653
model-prepare is a skill published in the GitHub repository apache/magpie (120 stars, last pushed today), licensed Apache-2.0. It adds 66 tokens to every session and 4,673 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.
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