principle-encode-lessons-in-structure
Apply when you catch yourself writing the same instruction a second time, or notice a recurring correction.
Skill by dyegolara
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/dyegolara-principle-encode-lessons-in-structure
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: writing
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What's inside
- Skill name
principle-encode-lessons-in-structure- Description
- Apply when you catch yourself writing the same instruction a second time, or notice a recurring correction. Encode the rule as a lint, metadata flag, runtime check, or script instead of more text.
- License
- MIT
- Metadata
- upstream: https://github.com/cursor/plugins/tree/main/pstack · upstream-path: pstack/skills/principle-encode-lessons-in-structure/SKILL.md · upstream-commit: f5bdd6826fd0a0d9cbc4347134c3a74a200b9d9d
- Instructions
- 27 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Encode Lessons in Structure
Encode recurring fixes in mechanisms (tools, code, metadata, automation) instead of textual instructions. Every error, human correction, and unexpected outcome is a learning signal. Capture it, route it, and close the loop.
**Why:** Textual instructions are easy to miss. They require the reader to notice, remember, and comply. Structural mechanisms (lint rules, metadata flags, runtime checks, automation scripts) enforce the rule without cooperation.
**Pattern:**
When you catch yourself writing the same instruction a second time:
1. Ask: can this be a lint rule, a metadata flag, a runtime check, or a script?
2. If yes, encode it. Delete the instruction
3. If no (requires judgment), make the instruction more prominent and add an example of the failure mode
**Pick the strongest mechanism.** When more than one mechanism would work, choose the strongest the situation allows (an unrepresentable state that cannot compile, then a lint or banned API that fails CI, then a canonical helper, then a runtime check), because agents copy whatever the surrounding code already does and a weaker guard becomes the next template.
**Corollary:** If the fix is structural, only use the structural fix. The instruction is the symptom.
**Feedback loop:**
- **Capture every correction.** When the human intervenes or tests fail, decide if it's a one-off or a pattern.
- **Route to the right layer.** One-off -> brain note. Recurring fix -> skill or lint rule. Systemic issue -> principle.
- **Close the loop.** Don't just record. Apply now or create a concrete todo.
**Anti-patterns:**
- Acknowledging without recording ("I'll keep that in mind" does not persist)
- Recording without routing (a brain note about a lint rule that should exist is wasted unless the lint rule gets implemented)
- Fixing without generalizing (fixing one instance while leaving the recurring pattern intact)From dyegolara/skillbook, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 35
- Last commit (this folder)
- Sep 15, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/dyegolara/skillbook
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
principle-encode-lessons-in-structure skill. Agent Mart. https://agentmart.dev/skills/dyegolara-principle-encode-lessons-in-structure (last updated 2026-10-24)