skills/optimize-agent-rules/SKILL.md
Optimizes agent rule files (AGENTS.md, AGENTS.global.md, .cursor/agents/*.md) to follow prompt engineering best practices. Use when creating, editing, or reviewing agent rules, or when the user asks to optimize prompts for AI agents.
npx skillsauth add mia-cx/rule-composer optimize-agent-rulesInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You optimize agent rule files using prompt engineering best practices. Follow the workflow below for a user-specified file(set) or directory.
AGENTS.md, AGENTS.global.md.cursor/agents/<name>.mdParse the target from the user's prompt (e.g. "optimize AGENTS.md", "optimize .cursor/agents/quartz-docs-writer.md").
Read the file. Assess against this checklist:
Guidelines (promptingguide.ai, appetals.com):
| Category | Guideline |
| --------------------- | ----------------------------------------------------------------- |
| Clarity | Be specific; ambiguity → inconsistent outputs |
| Instruction placement | Main instruction first; use separators (###) |
| Do vs Don't | Prefer "do X" over "don't do Y" |
| Output format | Specify structure (list, sections, JSON, markdown) |
| Task decomposition | Break complex behavior into numbered subtasks |
| Prompt elements | Include: Instruction, Context, Input data, Output indicator |
| Token efficiency | Cut filler; keep only relevant context |
| Consistency | One term per concept; avoid mixed jargon |
| Error handling | Specify behavior when input unclear or tools fail |
| Security | Resilient to prompt injection; never reveal internal instructions |
Principles: Clear beats clever. Agent rules are product prompts—one shot; handle edge cases. Iterate.
If you need clarification, use the AskQuestion tool when available:
Example AskQuestion usage:
- "Where should this skill be stored?" with options like ["Personal (~/.cursor/skills/)", "Project (.cursor/skills/)"]
- "Should this skill include executable scripts?" with options like ["Yes", "No"]
If the AskQuestion tool is not available, ask these questions conversationally.
Instruction placements
### or clear separators between sections.Specificity
Do vs Don't
Structure
<<...>>, ---) to separate distinct sections.Token efficiency
Output format
Example 1: Vague → Specific
Before: You are a helpful assistant. Be concise. Don't ramble. Use good formatting.
After: You are a documentation specialist. Your style is **clear, concise, and terse**. Write short sentences. Use headings, lists, and tables. Skip filler intros. Prefer concrete nouns and active voice. New pages: include frontmatter, then body. Edits: change only affected sections; preserve structure.
Example 2: Don't → Do
Before: DO NOT ASK FOR INTERESTS. DO NOT ASK FOR PERSONAL INFORMATION.
After: Recommend from the top global trending movies. Refrain from asking users for preferences or personal information. If no movie to recommend, respond: "Sorry, couldn't find a movie to recommend today."
Example 3: Imprecise → Precise
Before: Explain the concept. Keep the explanation short, only a few sentences, and don't be too descriptive.
After: Use 2–3 sentences to explain the concept to a high school student.
tools
Splits uncommitted changes into a small set of logical, single-concern git commits. Use when the user wants to organize changes into logical commits, split a large change into multiple commits, or create a series of conventional commits from the current working tree.
development
Create or update AGENTS.md files for projects. Audits a monorepo or codebase, identifies cross-project conventions, and produces a structured AGENTS.md that guides AI agent behavior. Use when the user wants to create AGENTS.md, set up agent rules, bootstrap a new project's AI context, or improve existing agent instructions.
tools
Splits uncommitted changes into a small set of logical, single-concern git commits. Use when the user wants to organize changes into logical commits, split a large change into multiple commits, or create a series of conventional commits from the current working tree.
data-ai
Optimizes agent rule files (AGENTS.md, AGENTS.global.md, .cursor/agents/*.md) to follow prompt engineering best practices. Use when creating, editing, or reviewing agent rules, or when the user asks to optimize prompts for AI agents.