agent-harness-design
Designing agent harnesses and tool systems — risk taxonomy for tools, permission decisions, draft/commit pattern, structured tool…
On-demand minimalism intensifier — find the smallest sufficient, verified implementation for the requested outcome. Use when the user says "be lazy / yagni / simplest / minimal / shortest / don't over-engineer", complains about bloat / boilerplate / unnecessary dependencies /
$ npx -y skills add AnastasiyaW/codex-claude-code-config --skill lean-code --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/lean-codeContext preview
The summary Claude sees to decide when to auto-load this skill.
On-demand minimalism intensifier — find the smallest sufficient, verified implementation for the requested outcome. Use when the user says "be lazy / yagni / simplest / minimal / shortest / don't over-engineer", complains about bloat / boilerplate / unnecessary dependencies /
name: lean-code description: >- On-demand minimalism intensifier — find the smallest sufficient, verified implementation for the requested outcome. Use when the user says "be lazy / yagni / simplest / minimal / shortest / don't over-engineer", complains about bloat / boilerplate / unnecessary dependencies / abstraction, or before writing a substantial chunk of new code. Supports intensity: lite / full / ultra. Pairs with the always-on quality-code rule and the over-engineering-advisor hook. Do NOT use as a general code-review or bug-hunting pass — it only removes over-building and will not find unrelated correctness defects; use /code-review or /review for those.
Aggressive YAGNI mode, on demand. The always-on baseline is `rules/quality-code.md`; this skill is the **intensifier** you invoke when minimalism matters most. The win is the smallest solution that fully satisfies the accepted task outcome, not the fewest lines or the shortest explanation.
Choose a rung only when it preserves the accepted architecture, contracts, and non-functional requirements; installed/native status alone does not justify crossing an established project boundary.
1. **Does this need to exist at all?** Speculative need → skip it, say so in one line. (YAGNI) 2. **Stdlib does it?** Use it. 3. **Native platform feature covers it?** (`<input type="date">` over a picker lib, CSS over JS, a DB constraint over app code.) 4. **An already-installed dependency solves it?** Use it. Never add a new dependency for what a few lines do. 5. **Can the accepted behavior safely be one line?** Prefer it; do not contort control flow, validation, or errors merely to make it fit. 6. **Only then** — the minimum code that works.
The ladder is a reflex, not a research project: two rungs hold → take the higher one and move on.
Input validation at trust boundaries · error handling that prevents data loss · security · accessibility · the calibration real hardware needs · anything the user explicitly asked to keep. **Lean ≠ incomplete:** non-trivial logic leaves one runnable check behind (assert-demo or one small test). User insists on the full version → build it, no re-arguing.
This is orthogonal to thoroughness. "Minimal" means less unnecessary complexity while delivering every accepted branch, not fewer branches done, a lower line count, or a shortcut. It must never excuse under-delivery, skipped verification, or a hack — see `rules/finish-the-task.md` (its completeness + quality pillars win) and `rules/quality-code.md` (the no-monkey-patch pole). Mark a deliberate shortcut with a `simplification:` comment naming the ceiling + upgrade path.
Complete and verify the requested result first. Then use at most three short lines for what was deliberately skipped and the trigger to add it. Do not suppress an explanation needed to document a safety boundary, user decision, or upgrade path. Read the surrounding code and requirements before pruning — prune to the task, not to a blanket rule.
GitClear's 2025 report observed rising copy/paste and falling moved-line rates across 211M changed lines; Faros observed higher team task/PR throughput alongside slower review and no demonstrated organization-wide gain. Those are ecosystem signals, not proof that a particular agent or diff is bloated. A "do I even need this?" check is therefore useful, but not a line-count target. [GitClear](https://gitclear-public.s3.us-west-2.amazonaws.com/GitClear-AI-Copilot-Code-Quality-2025.pdf) · [Faros](https://www.faros.ai/blog/ai-software-engineering)
Generic prompt additions can trade one measured behavior for another in small local experiments; they do not establish a universal minimalism rule. Keep this on-demand and advisory, then evaluate its instructions on representative held-out tasks. [arXiv:2601.22025](https://arxiv.org/abs/2601.22025)
A practical configuration kit for Claude Code, Codex, and other coding agents. It contains architectural principles, enforcement hooks, skills, drop-in rules, starter templates, and dynamic-workflow commands.
Designing agent harnesses and tool systems — risk taxonomy for tools, permission decisions, draft/commit pattern, structured tool…
Use when designing, auditing, refactoring, or explaining an agentic harness for any domain, especially when work must continue…
Практическая инженерия диффузионных моделей: архитектуры, обучение, инференс, оптимизация памяти. Использовать при любых задачах…
Expert prompt engineering for FLUX.2 [klein] image generation and editing model. Use this skill whenever the user wants to create…
Plan or review LoRA and edit-training work specifically for FLUX.2 Klein or Qwen-Image-Edit, including paired datasets,…
Forensic image-to-prompt compiler for image generation models. Use this skill whenever the user wants to: convert/describe an…