skill-evaluation-and-iteration-with-codex
Score, diagnose, and rewrite underperforming AI agent skills to improve triggering and reliability.
- Score existing skills against a strict 9-point quality rubric
- Fix inconsistent agent behavior by refining output contracts and boundaries
- Update legacy Agensi skills to modern Codex and OpenAI metadata standards
Secure checkout via Stripe
Included in download
- Score existing skills against a strict 9-point quality rubric
- Fix inconsistent agent behavior by refining output contracts and boundaries
- file_read, file_write, terminal automation included
- Ready for Claude
Sample Output
A real example of what this skill produces.
SKILL EVALUATION REPORT: [image-optimizer-v2] OVERALL SCORE: 6.4/10 ROOT CAUSE: Triggering is too vague; the agent misidentifies CSV files as images. PLAN:
- Rewrite Trigger Conditions to exclude non-image extensions.
- Define Output Contract for WebP conversion.
- Patch SKILL.md.
skill-evaluation-and-iteration-with-codex
Score, diagnose, and rewrite underperforming AI agent skills to improve triggering and reliability.
Secure checkout via Stripe
Included in download
- Score existing skills against a strict 9-point quality rubric
- Fix inconsistent agent behavior by refining output contracts and boundaries
- file_read, file_write, terminal automation included
- Ready for Claude
- Instant install
Sample Output
A real example of what this skill produces.
SKILL EVALUATION REPORT: [image-optimizer-v2] OVERALL SCORE: 6.4/10 ROOT CAUSE: Triggering is too vague; the agent misidentifies CSV files as images. PLAN:
- Rewrite Trigger Conditions to exclude non-image extensions.
- Define Output Contract for WebP conversion.
- Patch SKILL.md.
About This Skill
Analyze and Optimize Your AI Agent Skills
Developing high-quality AI agent skills requires more than just a good prompt. This skill is a developer's diagnostic tool for auditing, scoring, and refining existing SKILL.md files. It bridges the gap between a "functional" skill and a "marketplace-ready" product by identifying why a skill might be failing to trigger, producing inconsistent results, or lacking clear boundaries.
What it does
- Quantitative Scoring: Evaluates skills across 9 dimensions including Purpose, Triggering, Guardrails, and Codex Compatibility using a strict 1-10 rubric.
- Root Cause Analysis: Pinpoints structural failures like placeholder output templates, vague procedures, or over-broad permission scopes.
- Automated Refinement: Generates a prioritized improvement plan and can directly patch files to bring older skills up to modern Codex and OpenAI standards.
- Validation: Integrates with local validation scripts to ensure frontmatter and file structures meet distribution requirements.
Why use this skill
Prompting an AI to "improve my skill" often results in generic advice. This skill operates as a specialized auditor that understands the specific architecture of Agentic frameworks. It ensures your SKILL.md is written as an executable procedure rather than a list of suggestions, significantly increasing the reliability and conversion rate of your agentic tools.
📖 Learn more: Best Testing & QA Skills for Claude Code →
Use Cases
- Score existing skills against a strict 9-point quality rubric
- Fix inconsistent agent behavior by refining output contracts and boundaries
- Update legacy Agensi skills to modern Codex and OpenAI metadata standards
- Generate prioritized rewrite plans to increase skill marketplace conversion
How to Install
mkdir -p ~/.claude/skills && curl -sL https://www.agensi.io/api/install/skill-evaluation-and-iteration-with-codex | tar xz -C ~/.claude/skills/Free skills install directly. Paid skills require purchase - use the download button above after buying.
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Security Scanned
Passed automated security review
Permissions
File Scopes
**Permission Profile:** Read + Write documentation
This skill is optimized for Codex acting on local skill files. It can review Grok, Claude, ChatGPT, Cursor, and portable Agensi skills, but Codex-specific validation applies only to Codex skill folders.
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