Official · GitHub CopilotFreeSummary Design error recovery for gh-aw workflows, including failed installations and API calls. Define retry limits, increasing wait times, error categories, and debug logs to handle temporary failures and prevent endless retries.
- Add bounded retries to network operations
- Plan recovery from installation failures
- Handle GitHub API rate limits
github/gh-aw☆ 5.4KUpdated Oct 21, 2026
5-level error recovery escalation: retry, nudge, replan, fallback, force-done — each with entry criteria and timeout before escalating
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oimiragieo/agent-studio☆ 42Updated Jul 14, 2026
Investigate failing tests, broken builds, and unexpected behavior through a structured debugging process. Reproduce the failure, narrow down its source, fix the root cause, and add a regression test that catches the same problem.
- Investigating a test that fails after a code change
- Finding the cause of a broken build
- Tracing a feature that stopped working
addyosmani/agent-skills☆ 109.2KUpdated Oct 14, 2026
Design recovery paths for AI agents that loop, lose streamed responses, or hit service limits. Classify failures, choose retries or backup models, and set stopping rules to keep recovery attempts from causing further failures.
- Investigating repeated tool calls with no progress
- Designing recovery for interrupted responses
- Setting retry limits and stopping rules
bojieli/ai-agent-book☆ 55.3KUpdated Oct 9, 2026
Handle failed tool calls with a clear recovery process. The skill distinguishes temporary problems from input or setup issues, chooses whether to retry or change approach, and records failures so unsuccessful tasks are not silently lost.
- Deciding whether to retry a failed tool call
- Correcting inputs after setup or validation errors
- Switching approaches after repeated tool failures
aden-hive/hive☆ 11.1KUpdated Oct 20, 2026
Troubleshoot unclear errors when converting documents to PDF with pandoc. Check installation, capture error logs, identify missing fonts or packages, and try alternative PDF engines, the tools that render the final document.
- Investigating an unknown error during PDF conversion
- Checking missing fonts and LaTeX packages
- Retrying conversion with a different PDF engine
HKUDS/OpenSpace☆ 7.8KUpdated Aug 13, 2026
Official · GitHub CopilotFreeSummary Guide agents through failures with timed retries, alternative methods, targeted fixes, and clear handoffs. It also explains when to continue with partial results, helping teams choose a recovery approach that fits the problem.
- Retrying temporary API and network failures
- Switching methods when a tool fails
- Diagnosing build and test errors
github/gh-aw☆ 5.4KUpdated Oct 21, 2026
Standard recovery patterns for all squad agents. When something fails, adapt — don't just report the failure.
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microsoft/waza☆ 1.4KUpdated Oct 21, 2026
Guides systematic root-cause debugging. Use when tests fail, builds break, something that worked yesterday broke, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need to figure out what broke and why — a systematic approach to finding and fixing the root cause rather than guessing.
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nota-america/forgecat-agent-profiles☆ 92Updated Sep 24, 2026
Standard recovery patterns for all squad agents. When something fails, adapt — don't just report the failure.
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jguadagno/jjgnet-broadcast☆ 18Updated Aug 4, 2026
Guides systematic root-cause debugging. Use when tests fail, builds break, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need a systematic approach to finding and fixing the root cause rather than guessing.
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manu14357/zskills☆ 16Updated Jul 24, 2026
Diagnoses and fixes bugs, type errors, lint failures, CI/CD issues, and runtime errors via root-cause-first investigation. Use for defect remediation. NOT for investigation without a fix (see mk:investigate); NOT for build-only compilation errors (see mk:build-fix).
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ngocsangyem/MeowKit☆ 15Updated Jul 28, 2026
Guides systematic root-cause debugging. Use when tests fail, builds break, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need a systematic approach to finding and fixing the root cause rather than guessing.
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kevinnft/ai-agent-skills☆ 14Updated Aug 1, 2026
Guides systematic root-cause debugging. Use when tests fail, builds break, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need a systematic approach to finding and fixing the root cause rather than guessing.
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mouadja02/skills☆ 10Updated Oct 21, 2026
Guides systematic root-cause debugging. Use when tests fail, builds break, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need a systematic approach to finding and fixing the root cause rather than guessing.
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Agistra/agistra.dev☆ 5Updated Oct 19, 2026