agent-harness-construction
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
npx skills add mturac/everything-openai-codex --skill agent-harness-construction --agent codex
Same command for any agent — swap --agent for claude-code, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Agent Harness Construction Use this skill when you are improving how an agent plans, calls tools, recovers from errors, and converges on completion. ## Core Model Agent output quality is constrained by: 1. Action space quality 2. Observation quality 3. Recovery quality 4. Context budget quality ## Action Space Design 1. Use stable, explicit tool names. 2. Keep inputs schema-first and narrow. 3. Return deterministic output shapes. 4. Avoid catch-all tools unless isolation is impossible. ## Granularity Rules - Use micro-tools for high-risk operations (deploy, migration, permissions). - Use medium tools for common edit/read/search loops. - Use macro-tools only when round-trip overhead is the dominant cost. ## Observation Design Every tool response should include: - `status`: success|warning|error - `summary`: one-line result - `next_actions`: actionable follow-ups - `artifacts`: file paths / IDs ## Error Recovery Contract For every error path, include: - root cause hint - safe retry instruction - explicit stop condition ## Context Budgeting 1. Keep system prompt minimal and invariant. 2. Move large guidance into skills loaded on demand. 3. Prefer references to files over inlining lo
- Core Model
- Action Space Design
- Granularity Rules
- Observation Design
- Error Recovery Contract
- Context Budgeting
- Architecture Pattern Guidance
- Benchmarking
- Anti-Patterns
What does the agent-harness-construction skill do?
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
How do I install it?
Run `npx skills add mturac/everything-openai-codex --skill agent-harness-construction --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mturac/everything-openai-codex, a repository with 84 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.