prompt-optimizer
Skill2 starsChanged 7 months agoNo licenceView on GitHub
Use when improving a prompt, rewriting a prompt for better results, generating a prompt from a brief, adapting a prompt for a specific model, diagnosing why a prompt is failing, or producing prompt variants for speed, quality, extraction, reasoning, or creativity. Optimizes rough, under-specified, or inconsistent prompts into stronger prompts with clearer instructions, context, constraints, examples, and output schemas.
72 other projects use a version of this.
Adopted by
Most recently taken up by
- Rojios/everything-claude-codetheir own version, first seen Nov 8, 2026
- ahmadvahidi/skill-atlastheir own version, first seen Nov 8, 2026
- Samuel-Shek/prompt-optimizertheir own version, first seen Nov 8, 2026
- EchoUser005/prompt-optimizertheir own version, first seen Nov 8, 2026
- dreamor/prompt-optimizer-skilltheir own version, first seen Nov 8, 2026
- rodeyseijkens/skillstheir own version, first seen Nov 6, 2026
Used with
Projects with it also use agent-architecture-audit, continuous-agent-loop and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
ronmkrSkillagent-architecture-audit
Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature.
Also in 3 projects that use this
junimnjwSkillcontinuous-agent-loop
Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.
Also in 3 projects that use this
- junimnjwSkill
agent-harness-construction
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
Also in 3 projects that use this
get-proofpilotSkillcontext-budget
Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations.
Also in 5 projects that use this
LangChainSkilldocker-patterns
Best practices for Docker containerization and multi-stage builds
Also in 4 projects that use this
royaluniondesign-sysSkilldeployment-patterns
Deployment workflows, CI/CD pipeline patterns, Docker containerization, health checks, rollback strategies, and production readiness checklists for web applications.
Also in 3 projects that use this
Other versions72 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 72
- github/awesome-copilot★ 41ksame name
- daymade/claude-code-skills★ 1.5ksame name
- getsentry/skills★ 1.1ksame name
- chujianyun/skills★ 751same name
- Cranot/roam-code★ 517same name
- loulanyue/awesome-claude-notes★ 272same name
- Fmarzochi/EGC★ 61same name
- drvoss/everything-copilot-cli★ 48same name
- khalilbenaz/claude-skills-collection★ 28same name
- kunwl123456/zeroclaw-skills-collection★ 27same name
62 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
Show its rules and text
We split this skill into the rules it gives an agent
28 rules. 0 are common, 28 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 58 edited versions we read keep these.
28
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
“Common” is measured: kept by at least 6 in 10 of the 58 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
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