blueprint-figure
Draws static SVG figures for lessons, READMEs and manuals in the AI Engineering from Scratch look: paper panel, blueprint accent,…
Build, audit, and improve harnesses that make AI coding agents reliable: AGENTS.md/CLAUDE.md instruction files, feature/state tracking, verification gates, scope boundaries, session handoff, memory persistence, context budgets, tool-permission safety, and multi-agent
Claude Code
$ npx -y skills add walkinglabs/learn-harness-engineering --skill harness-creator --agent claude-code
Codex
$ npx skills add walkinglabs/learn-harness-engineering --skill harness-creator -a codex -y
Cursor
$ npx skills add walkinglabs/learn-harness-engineering --skill harness-creator -a cursor -y
Gemini CLI
$ npx skills add walkinglabs/learn-harness-engineering --skill harness-creator -a gemini-cli -y
GitHub Copilot
$ npx skills add walkinglabs/learn-harness-engineering --skill harness-creator -a github-copilot -y
OpenCode
$ npx skills add walkinglabs/learn-harness-engineering --skill harness-creator -a opencode -y
Windsurf
$ npx skills add walkinglabs/learn-harness-engineering --skill harness-creator -a windsurf -y
name: harness-creator description: >- Build, audit, and improve harnesses that make AI coding agents reliable: AGENTS.md/CLAUDE.md instruction files, feature/state tracking, verification gates, scope boundaries, session handoff, memory persistence, context budgets, tool-permission safety, and multi-agent coordination. Use this whenever a coding agent is unreliable across sessions — forgets context, drifts out of scope, claims "done" before tests pass, or starts each session inconsistently — or when creating or assessing AGENTS.md, CLAUDE.md, feature_list.json, init.sh, progress.md, or session-handoff files. Reach for it even if the user never says the word "harness." license: MIT
Use this skill to make a repository easier for coding agents to start, stay in scope, verify work, and resume across sessions. Keep the harness small enough that agents actually follow it.
Not for model selection, prompt tuning in isolation, chat UI design, or general app architecture.
Every useful coding-agent harness has five subsystems:
| Subsystem | Minimal artifact | Purpose | |---|---|---| | Instructions | `AGENTS.md` or `CLAUDE.md` | Startup path, working rules, definition of done | | State | `feature_list.json`, `progress.md` | Current feature, status, evidence, next step | | Verification | `init.sh` or documented commands | Tests/checks the agent must run before claiming done | | Scope | Feature dependencies and done criteria | Prevents overreach and half-finished work | | Lifecycle | `session-handoff.md`, end-of-session routine | Makes the next session restartable |
1. Inspect what already exists: instruction files, feature/state files, verification commands, docs, package manifests. 2. Ask only for missing context that cannot be inferred safely: target agent, desired file name, tolerance for structure, and whether overwriting is allowed. 3. Prefer a minimal harness first. Add memory, tool safety, multi-agent, or benchmark details only when the user's problem calls for them.
Use the bundled script when working on a local repository:
node skills/harness-creator/scripts/create-harness.mjs --target /path/to/project
Options:
Then explain what was created and how the user should replace placeholder feature entries.
Run:
node skills/harness-creator/scripts/validate-harness.mjs --target /path/to/project
Report the five subsystem scores, the lowest-scoring area, and the first 2-3 changes that would improve reliability. Treat the lowest score as a candidate bottleneck; confirm with failures, logs, or task outcomes before claiming causality.
Use when the user wants a shareable assessment:
node skills/harness-creator/scripts/render-assessment-html.mjs --target /path/to/project node skills/harness-creator/scripts/run-benchmark.mjs --target /path/to/project --html /path/to/report.html
Be clear that this is a structural benchmark. The benchmark first runs a self-check — it scaffolds a throwaway harness and validates it, proving the bundled scripts work end-to-end — then scores the target and eval coverage. Real effectiveness still needs before/after agent sessions on representative tasks.
Load only the reference needed for the user's problem:
For a usable minimal harness, leave the target project with:
If you cannot create files, provide exact file contents and commands instead.
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