Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
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mouadja02/skills102026年10月17日 更新
免费在 GitHub 公开
swe-agent-issue-loop
Use when turning GitHub issues or bug reports into reproducible coding-agent repair loops with sandboxed execution, focused tests, patch generation, and regression verification.
中文简介正在准备中。当前显示原文说明。
查看安装方法包含的文件（3）
- SKILL.md3.3 KB
- references/agent-loop-checklist.md1.3 KB
- scripts/issue_repro_matrix.py2.0 KB
SKILL.md（原文）
安装前可以查看交给 AI 代理的指令内容。
SWE Agent Issue Loop
Use this skill to handle issue-driven software engineering tasks the way modern coding-agent benchmarks and production agent harnesses do: isolate the repository, reproduce the failure, edit narrowly, and verify with executable tests.
When To Use
Activate when the user asks to:
- Fix a GitHub issue, bug report, failing test, or CI failure
- Build a coding-agent benchmark task
- Convert an issue into a reproducible repair workflow
- Compare agent scaffolds on software engineering tasks
- Add guardrails around autonomous coding agents
Repair Loop
-
Frame the issue
- Extract expected behavior, observed behavior, affected files, environment, and acceptance criteria.
- Identify what evidence is missing before editing.
- Record any user constraints such as no refactor, no dependency changes, or no UI changes.
-
Build a reproduction
- Run the smallest relevant failing command.
- Prefer a focused test over full-suite execution.
- If no test exists, write or sketch one before implementation when feasible.
- Store command, result, and failure reason.
-
Patch narrowly
- Read the local code around the failing behavior.
- Change the smallest coherent surface.
- Avoid solving benchmark tasks by hardcoding issue text, test names, or environment-specific values.
-
Verify
- Re-run the reproducer.
- Run adjacent tests or a targeted suite.
- Check for formatting, lint, type, or build regressions when relevant.
- Summarize command outcomes in the final response.
-
Harden the harness
- Use sandboxed execution for autonomous agents.
- Cap command timeouts and output length.
- Separate model instructions from tool output.
- Preserve full trajectories for later review.
Benchmark-Aware Guidance
SWE-bench Verified emphasizes clear issue descriptions, correct tests, and solvable tasks. Mirror that standard for internal benchmarks:
- Do not include ambiguous reports without expected behavior.
- Do not count a task as solved unless tests or deterministic checks pass.
- Track whether the agent used only allowed context.
- Capture the diff and trajectory, not only pass/fail.
Helper Script
Use issue_repro_matrix.py to convert issue text into a reproducibility matrix:
python scripts/issue_repro_matrix.py issue.md
References
Read agent-loop-checklist.md before designing a coding-agent harness or benchmark task.
External grounding:
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同一仓库的技能
Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
中文简介正在准备中。当前显示原文说明。
mouadja02/skills102026年10月17日 更新
Adds educational comments to a code file so it becomes a learning resource, asking for the file (with a list of close matches) if none is given. Use when preparing code for learners, onboarding, or teaching.
中文简介正在准备中。当前显示原文说明。
mouadja02/skills102026年10月17日 更新
Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
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mouadja02/skills102026年10月17日 更新
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
中文简介正在准备中。当前显示原文说明。
mouadja02/skills102026年10月17日 更新
Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
中文简介正在准备中。当前显示原文说明。
mouadja02/skills102026年10月17日 更新