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 agentmods add skills/apache/magpie/issue-reproducernpx skills add apache/magpie --skill issue-reproducergit 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/issue-reproducer)<a href="https://agentmods.dev/skills/apache/magpie/issue-reproducer"><img src="https://agentmods.dev/badge/skills/apache/magpie/issue-reproducer.svg" alt="Measured on agentmods" 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 | $0.00110 | $0.05957 |
| Opus 5 | $0.00055 | $0.02978 |
| Sonnet 5 | $0.00022 | $0.01191 |
| Haiku 4.5 | $0.00011 | $0.00596 |
Grade A, and why
magpie-issue-reproducer 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 — 536 lines — stays where its author put it; the contents beside it link to each section on GitHub.
issue-reproducer
Use this skill when the job is to take an issue-described problem
and actually run it: find the reproducer code, work out what shape
it's in, adapt it to a runnable form, and execute it against the
current <default-branch> and the project's runtime with enough
evidence captured that a maintainer can trust the verdict without
redoing the work.
This skill is the load-bearing piece for both single-issue triage (when a stronger-than-eyeballed reproduction is wanted) and bulk reassessment campaigns. It doesn't speak about workflow, batch processing, or hand-back — those belong to the calling skills:
issue-triage— invokes this skill at the "attempt reproduction on<default-branch>" step when a classification hinges on runtime evidence.issue-reassess— bulk reassessment campaign; calls this skill for every issue in the candidate set.issue-fix-workflow— when the reproducer adapts cleanly to a regression test, the fix-workflow skill takes the adapted form as its starting point.
Golden rules
Golden rule 1 — never fabricate. "The reporter described X
happening; I'll write code that does X." That is the agent doing
the reporter's job. If the description is prose-only and no
attachment helps, classify cannot-run-extraction and stop. The
reporter's specific code is what makes a reproduction trustworthy;
an agent-written stand-in is a different exercise (and a different
verdict). The full anti-fabrication discipline lives in
extraction.md.
What ships with it
5 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.
- 5d ago First seen · 536 lines · 110 tokens per session scan A 17806ac997a5
magpie-issue-reproducer is a skill published in the GitHub repository apache/magpie (87 stars, last pushed 3d ago), licensed Apache-2.0. It adds 110 tokens to every session and 5,957 once invoked, about $0.0006 per session on Opus 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 2026-08-30.
Other skills, from other repositories
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aip-user-stories
Generate verified recipe playbooks from AIPs with PR implementations (post mode), or speculative user stories from AIPs without implementations (pre mode). Use when the user provides an AIP URL or AIP content, optionally with PR URLs and file paths.
airflow-new-sdk
Guide for implementing a brand-new language SDK for Airflow (AIP-108). Use this skill when a contributor wants to add support for a new programming language — designing the Python coordinator, implementing the wire protocol in the target language, writing the bundle format, and structuring the PR. Trigger on phrases…
airflow-java-sdk
Guide for contributing to the Airflow Java SDK (AIP-108). Use this skill whenever a contributor is working in the java-sdk/ directory or on the Java coordinator in task-sdk/src/airflow/sdk/coordinators/java/ — whether they want to add a feature, write tests, fix a bug, understand the architecture, or prepare a PR.…
aip-tracker
Track Airflow Improvement Proposal (AIP) implementation progress by comparing Confluence specs against codebase evidence. Use when asked to assess, report on, or compare AIP status.