Agent skill · Testing & QA

experiment-iterative-coder

Iterative code refinement through plan → code → evaluate → refine cycles. Runs lint checks (ruff), tests (pytest), and structured self-evaluation each cycle, then diagnoses failures and refines. Decomposes complex tasks into sequential phases, iterates up to 3 times per phase (10 total). Use when: the main agent delegates a code task with 'MODE: MORE_EFFORT', the user selects 'More Effort' code generation mode, or the task explicitly requests iterative refinement for higher code quality. Do NOT use for single-pass code generation (Lite mode), experiment pipeline orchestration (use experiment-p

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codecan modify filesNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill experiment-iterative-coder --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 10 KB
Bundled scripts: none
Version: 1.0.0
Declared author: EvoScientist
Allowed tools: write_fileedit_fileread_filethink_toolexecute
Path: skills/evoskills/experiment-iterative-coder/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Iterative Coder Iterative code refinement through structured plan → code → evaluate → refine cycles. Each cycle runs objective checks (lint, tests) and self-evaluation, then diagnoses failures and plans targeted improvements. Reaches production quality in 3-8 iterations. ## When to Use This Skill - Main agent delegates a code task prefixed with "MODE: MORE_EFFORT" - User selected "More Effort" mode for code generation - Task requires high code quality with verified correctness - Task involves complex implementation (5+ files, multiple modules) - You want to iterate on code quality rather than submit first-pass code - You mention "iterative refinement", "code quality loop", "plan-code-evaluate" ## The Iteration Mindset **Code quality comes from fast feedback loops, not careful first attempts.** A fast plan → code → evaluate → fix cycle beats spending 30 minutes on a "perfect" first implementation. The evaluate step reveals problems you cannot predict by thinking alone — lint errors, import failures, test regressions, and missing edge cases all surface immediately when you actually run the code. ## Before Starting: Load Context 1. Read `/memory/experiment-memory.md` for proven stra

What's inside
Steps it walks through
  1. When to Use This Skill
  2. The Iteration Mindset
  3. Before Starting: Load Context
  4. Phase Decomposition
  5. The Iteration Loop
  6. Step 1: Plan
  7. Step 2: Code
  8. Step 3: Evaluate
  9. Step 4: Score
  10. Step 5: Decide
  11. Step 6: Log
  12. Completion
  13. Counterintuitive Iteration Rules
  14. Skill Integration
Commands it runs
ruff --version 2>&1; echo "---"; python -m pytest --version 2>&1
ruff check . 2>&1 | tail -20
echo "LINT_EXIT: $?"
ruff format --check . 2>&1 | tail -10
echo "FORMAT_EXIT: $?"
python -m pytest -x -q --tb=short 2>&1 | tail -30
echo "TEST_EXIT: $?"
More from awesome-bio-agent-skills
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About this skill
What does the experiment-iterative-coder skill do?

Iterative code refinement through plan → code → evaluate → refine cycles. Runs lint checks (ruff), tests (pytest), and structured self-evaluation each cycle, then diagnoses failures and refines. Decomposes complex tasks into sequential phases, iterates up to 3 times per phase (10 total). Use when: the main agent delegates a code task with 'MODE: MORE_EFFORT', the user selects 'More Effort' code generation mode, or the task explicitly requests iterative refinement for higher code quality. Do NOT use for single-pass code generation (Lite mode), experiment pipeline orchestration (use experiment-p

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill experiment-iterative-coder --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 BioTender-max/awesome-bio-agent-skills, a repository with 135 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.

Keep going