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QualityTypeScript

Execute Feedback

Execute Feedback is a Quality skill for Claude Code, published by jmagly in aiwg.

209 stars32 forkson jmagly/aiwgAdded 2026/09/04+1% in starsRepository updated 2026/09/03

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agentic-codingai-frameworkanthropicautonomous-agentsclaude-codecodexcopilotcursordeveloper-toolsfine-tuningmulti-agentmulti-platformorchestrationprompt-engineeringsdlctraining-datawarpworkflow-automation

Install in seconds

Install Execute Feedback

Copy Execute Feedback into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/jmagly/aiwg/tree/main/agentic/code/addons/agent-loop/skills/execute-feedback ~/.claude/skills/execute-feedback

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/jmagly/aiwg.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: agentic/code/addons/agent-loop/skills/execute-feedback/SKILL.md in jmagly/aiwg
Installs to: ~/.claude/skills/execute-feedback
Collection: One of 25 skills cataloged from this repository
Category: Quality — 1557 skills

What Execute Feedback does

Execute Feedback runs tests on generated code, analyzes failures, applies targeted fixes, and retries until the code passes or max attempts are reached. Use it after code generation or edits to verify behavior.

Execute Feedback is cataloged under Quality on DirSkills. Execute Feedback comes from a repository tagged agentic-coding, ai-framework, anthropic, autonomous-agents and claude-code.

Documentation

README

Excerpt

Execute Feedback Command

Run executable feedback loop on generated code: execute tests, analyze failures, fix, and retry.

Instructions

When invoked, perform the executable feedback loop per REF-013 MetaGPT:

Identify Target
- Load the specified file or recently modified code files
- Determine test framework (jest, pytest, cargo test, go test, etc.)
- Find existing tests or generate test stubs if none exist
Execute Tests
- Run the specified test command (or auto-detect)
- Capture full output (stdout, stderr, exit code)
- Parse test results: passed, failed, errors, skipped

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Execute Feedback

What else does jmagly publish alongside Execute Feedback?
Execute Feedback is one of 25 skills that DirSkills catalogs from jmagly/aiwg, the repository it ships in. Its siblings there include Agent Loop, Agent Loop and Agent Loop External. Each one is a separate skill with its own page in this directory, installs the same way Execute Feedback does, and is maintained by jmagly in that same repository. The rest of the collection is listed on the jmagly/aiwg page.
How does Execute Feedback compare to other Quality skills?
Execute Feedback ranks #1450 by stars among the 1557 Quality skills in this catalog. The most-starred ones next to it are Benchmark, Benchmark Optimization Loop and API Design Patterns. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Execute Feedback against them. Open each page to compare what they document and how they install.

More from jmagly/aiwg

Execute Feedback is one of 25 skills cataloged on DirSkills from jmagly/aiwg.

See all 25 skills →

Agent Loop

Agent Loop detects requests for iterative autonomous task execution and routes them to the right loop executor. Use it when a user wants to keep trying, fix until green, or run an explicit agent loop.

Agent Loop

Agent Loop executes a task in repeated cycles until verifiable completion criteria are met. Use it when you want an agent to keep trying, learn from failures, and report the final status.

Agent Loop External

Agent Loop External launches a long-running agent loop outside the current session with saved state. Use it for crash recovery, parallel runs, and CI/CD-backed tasks that need resumable execution.

Agent Persistence

Agent Persistence defines reusable human-in-the-loop gates for persistent agent loops. Use it when you need authorization for destructive actions, policy overrides, or recovery escalation.

Al External

Al External launches long-running iterative loops outside the AI session with saved state. Use it for tasks that need crash recovery, parallel runs, or CI/CD integration.

Al Memory

Al Memory lets you list, query, and clear semantic memory entries from loop iterations. Use it to review lessons learned, failure patterns, and success patterns across runs.

More Quality skills

Execute Feedback is one of 1557 Quality skills cataloged on DirSkills, ranked #1450 by stars among them.

Browse all Quality skills →

Benchmark

Benchmark measures performance baselines, detects regressions before and after PRs, and compares stack alternatives for pages, APIs, and builds.

Benchmark Optimization Loop

Benchmark Optimization Loop turns vague performance goals into a bounded, measured optimization process. Use it when asked to make something faster, benchmark latency/throughput/cost, or choose the best implementation by repeated measured tests.

API Design Patterns

API Design Patterns provides conventions and best practices for designing consistent REST APIs. Use it when creating endpoints, reviewing contracts, handling pagination, error responses, status codes, filtering, or versioning.