correct
Eliminate repeated agent mistakes at the highest level that works: architecture, types, lint, tests, docs last.
Skill by TudeOrangBiasa
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/tudeorangbiasa-correct
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About
Use cases: agent-building
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/correct
What's inside
- Skill name
correct- Description
- Eliminate repeated agent mistakes at the highest level that works: architecture, types, lint, tests, docs last. Use each time a correction lands.
- License
- MIT
- Instructions
- 27 lines in SKILL.md · view on GitHub
Files (3)
- CREDITS.md
- SKILL.md
- openai.yaml · agents/
SKILL.md (first lines)
# Correct The operator keeps correcting agents in this repo for the same mistakes. Change the repo so the next agent cannot make them. Run this each time a correction lands; a repeated correction the skill did not prevent is the skill failing. Assume every contributor is an agent that sees only the files it opened, copies the nearest example, and takes the shortest path that compiles. Design so a change that looks right from one file is right for the whole repo. ## Find the mistake classes Read recent commits, reverts, review comments, instruction files, and comments explaining workarounds. Group mistakes into classes; a class counts once it has happened twice. ## Fix each class at the highest level that works 1. **Eliminate with architecture.** One owner per state, one supported way per task, internals hidden so the wrong import fails. Replace hand-synced lists with one source of truth. Delete old ways and dead code an agent would copy. 2. **Enforce with types, then lint.** Unrepresentable bad states first; where the bad code still compiles, add a lint or CI check whose error names the file, type, or function to use instead. Patterns already common fail only on growth (new additions), never the backlog. 3. **Test the behavior.** Write assertions against what the code's users can observe: the test fails when that observable behavior breaks and keeps passing when only internals change. 4. **Write docs or agent rules last, only for judgement calls.** Nothing fails when an agent skips them. ## Fix and prove Fix the most frequent classes now, one commit each. Prove each new check fails on a real past mistake; run the same command locally and in CI. Exceptions sit on the offending line with a reason, an expiry date, and a human's approval. ## Keep the rule table Keep a table in the repo's agent instruction file pairing each rule with its enforcer. On each new correction, fix the mistake and add the rule; a rule already there with nothing enforcing it is a repeat, so raise its level in the same change. Drop a rule once its mistake is impossible. **Reply:** each class with evidence, the level picked, and why a higher level did not work.
From TudeOrangBiasa/skills-for-agents, MIT.
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- 0.592score
diagnose
TudeOrangBiasa
Diagnosis loop for hard bugs and performance regressions.
SkillAFreshness: A★ 1Claude Code +9 - 0.589score
show-me-your-work
TudeOrangBiasa
Keep a reviewable decision trail for long or unattended work: TSV log per decision, end audit, cross-model attention flags.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
break
TudeOrangBiasa
Stress-test one component against worst-case content and states on a throwaway page, then report what visibly broke.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
setup-pre-commit
TudeOrangBiasa
Set up fast hooks with the repo's own toolchain (oxlint/oxfmt, Biome, or Prettier), type checking, tests, and a token-size gate.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
arena
TudeOrangBiasa
Parallel design bakeoff: N candidates on one brief, cross-judge, pick a base, graft the best parts.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
interrogate
TudeOrangBiasa
Adversarial multi-model review with rubric and bucketed verdict.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
architect
TudeOrangBiasa
Settle types, signatures, and module shape before code: ground, sketch twice, agree, implement, scrap when wrong.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
how
TudeOrangBiasa
Explain how a subsystem works: triage complexity, fan out explorers on 2 to 4 angles for complex scopes, synthesize into fixed sections.
SkillAFreshness: A★ 1Claude Code +9 - 0.579score
no-comments
TudeOrangBiasa
Kill needless comments plus the dead code they protect, fix root causes in scope, encode real constraints as structure.
SkillAFreshness: A★ 1Claude Code +9 - 0.562score
prototype
TudeOrangBiasa
Build a throwaway prototype to answer a design question.
SkillAFreshness: A★ 1Claude Code +9 - 0.562score
codebase-design
TudeOrangBiasa
Shared vocabulary for designing deep modules.
SkillAFreshness: A★ 1Claude Code +9 - 0.562score
domain-modeling
TudeOrangBiasa
Build and sharpen a project's domain model.
SkillAFreshness: A★ 1Claude Code +9
Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 1
- Last commit (this folder)
- Oct 22, 2026 (8 days ago)
- Last release
- Oct 23, 2026 (7 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from TudeOrangBiasa
- 0.592score
diagnose
TudeOrangBiasa
Diagnosis loop for hard bugs and performance regressions.
SkillAFreshness: A★ 1Claude Code +9 - 0.589score
show-me-your-work
TudeOrangBiasa
Keep a reviewable decision trail for long or unattended work: TSV log per decision, end audit, cross-model attention flags.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
arena
TudeOrangBiasa
Parallel design bakeoff: N candidates on one brief, cross-judge, pick a base, graft the best parts.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
break
TudeOrangBiasa
Stress-test one component against worst-case content and states on a throwaway page, then report what visibly broke.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
setup-pre-commit
TudeOrangBiasa
Set up fast hooks with the repo's own toolchain (oxlint/oxfmt, Biome, or Prettier), type checking, tests, and a token-size gate.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
interrogate
TudeOrangBiasa
Adversarial multi-model review with rubric and bucketed verdict.
SkillAFreshness: A★ 1Claude Code +9
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correct skill. Agent Mart. https://agentmart.dev/skills/tudeorangbiasa-correct (last updated 2026-10-24)