reviewing-agent-prompting
Review and improve prompts for coding agents. Use PROACTIVELY when auditing, checking, or evaluating agent instructions, system prompts, or task delegation text. Applies state-machine thinking to identify structural gaps and improve effectiveness.
Best use case
reviewing-agent-prompting is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Review and improve prompts for coding agents. Use PROACTIVELY when auditing, checking, or evaluating agent instructions, system prompts, or task delegation text. Applies state-machine thinking to identify structural gaps and improve effectiveness.
Teams using reviewing-agent-prompting should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/reviewing-agent-prompting/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How reviewing-agent-prompting Compares
| Feature / Agent | reviewing-agent-prompting | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Review and improve prompts for coding agents. Use PROACTIVELY when auditing, checking, or evaluating agent instructions, system prompts, or task delegation text. Applies state-machine thinking to identify structural gaps and improve effectiveness.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
<essential_principles> **Why structure matters:** LLMs hallucinate when they have too much freedom and too little structure. Vague prompts force the model to guess intent, approach, tools, and completion criteria. Each guess compounds uncertainty. **The core insight:** Treat prompts as state machines, not prose. Effective prompts have: - Entry conditions (what triggers this phase) - Actions (what to do) - Exit criteria (how to know it's complete) - Transitions (what comes next) **The paradox:** Rigid structure creates reliable autonomy. Constraints clarify; they don't limit. </essential_principles> <intake> **What would you like reviewed?** Provide the prompt text you want analyzed. This could be: - An agent system prompt - A task delegation prompt - Instructions for a coding assistant - Any prompt meant to guide autonomous behavior **Wait for the prompt text before proceeding.** </intake> <review_framework> **Phase 1: Structural Analysis** Check for these elements (present/absent/partial): **1. Request Classification** Does the prompt force categorization before action? **Strong pattern:** ``` Before acting, classify the request: - TYPE A (Simple): Single file, known location → direct action - TYPE B (Complex): Unknown scope → explore first - TYPE C (Research): External context needed → gather info ``` **Weak pattern:** No classification, jumps straight to action **Why it matters:** Classification prevents wrong-strategy application. A quick lookup shouldn't trigger comprehensive analysis. **2. Phase Gates with Exit Criteria** Are there explicit phases with completion conditions? **Strong pattern:** ``` ## Phase 1: Assessment - Check existing patterns - Review conventions **Exit criteria:** Know what patterns to follow before proceeding. ## Phase 2: Execution ... ``` **Weak pattern:** List of actions without phases or completion signals **Why it matters:** Without gates, agents skip steps or thrash. Exit criteria tell the agent when to move on. **3. Tool Constraints** Are tool permissions explicit and minimal? **Strong pattern:** ``` tools: Read, Grep, Glob (read-only, cannot modify) ``` **Weak pattern:** All tools available, or tools unspecified **Why it matters:** Constraints clarify. An agent that can't write files knows its purpose is analysis. **4. Mandatory Output Structure** Is output format required, not suggested? **Strong pattern:** ``` Every response MUST include: <findings>...</findings> <confidence>HIGH/MEDIUM/LOW</confidence> <next_steps>...</next_steps> Responses missing any section are incomplete. ``` **Weak pattern:** "Consider including..." or no format specified **Why it matters:** Required sections force completeness. The agent can't hand-wave. **5. Anti-Patterns (NEVER DO)** Are failure modes explicitly closed off? **Strong pattern:** ``` ## NEVER DO - Never suppress errors with workarounds - Never commit without running tests - Never guess file locations without searching ``` **Weak pattern:** Only positive instructions, no prohibitions **Why it matters:** Negative examples are as important as positive ones. They close off common failure modes. **6. Escalation Triggers** Does the prompt define when to stop and ask for help? **Strong pattern:** ``` Stop and escalate when: - 3 consecutive attempts have failed - Uncertainty exceeds 70% - Change would affect more than 5 files ``` **Weak pattern:** No acknowledgment of limits **Why it matters:** An agent that knows when to stop is more reliable than one that guesses forever. **7. First Action Clarity** Is the immediate first step crystal clear? **Strong pattern:** ``` When invoked: 1. Run git diff to see recent changes 2. Read each modified file 3. Begin analysis ``` **Weak pattern:** ``` When invoked: 1. Think about the problem 2. Consider options 3. Do something helpful ``` **Why it matters:** Agents need concrete starting points, not vague intentions. </review_framework> <scoring_rubric> **Structural Completeness Score** | Element | Weight | Criteria | |---------|--------|----------| | Request Classification | 15% | Forces explicit categorization before action | | Phase Gates | 20% | Clear phases with exit criteria | | Tool Constraints | 10% | Explicit, minimal permissions | | Output Structure | 15% | Mandatory format with required sections | | Anti-Patterns | 15% | NEVER DO section with specific prohibitions | | Escalation Triggers | 10% | Knows when to stop and ask | | First Action | 15% | Concrete immediate step | **Scoring:** - 0: Element absent - 1: Element present but weak - 2: Element present and strong **Interpretation:** - 12-14: Production-ready prompt - 8-11: Functional but could be more reliable - 4-7: Significant gaps, expect inconsistent behavior - 0-3: Essentially unstructured, high hallucination risk </scoring_rubric> <report_format> **Agent Prompt Review** **Summary** [One sentence assessment] **Structural Score: X/14** | Element | Score | Notes | |---------|-------|-------| | Classification | 0/1/2 | ... | | Phase Gates | 0/1/2 | ... | | Tool Constraints | 0/1/2 | ... | | Output Structure | 0/1/2 | ... | | Anti-Patterns | 0/1/2 | ... | | Escalation | 0/1/2 | ... | | First Action | 0/1/2 | ... | **Critical Issues** [Elements scoring 0 that should be added] **Improvements** [Elements scoring 1 that could be strengthened] **Strengths** [Elements scoring 2, what's working well] **Recommended Additions** [Specific text to add, with examples] </report_format> <example_review> **Input prompt:** ``` You are a helpful code assistant. Help the user with their code questions. Be thorough and accurate. ``` **Review:** ### Summary Minimal prompt with no structural elements. High hallucination risk. ### Structural Score: 1/14 | Element | Score | Notes | |---------|-------|-------| | Classification | 0 | No request typing | | Phase Gates | 0 | No phases | | Tool Constraints | 0 | Unspecified | | Output Structure | 0 | No format required | | Anti-Patterns | 0 | No prohibitions | | Escalation | 0 | No limits defined | | First Action | 1 | "Help" is vague but present | **Critical Issues** - No classification: Agent will apply same approach to simple lookups and complex research - No phases: Agent may skip directly to answers without gathering context - No output structure: Responses will be inconsistent **Recommended Additions** Add request classification: ``` Before responding, classify the request: - LOOKUP: Specific fact or syntax → answer directly - EXPLAIN: Understanding code → read and summarize - DEBUG: Something broken → investigate systematically - IMPLEMENT: Write new code → clarify requirements first ``` Add output structure: ``` Every response must include: <answer>Direct response to the question</answer> <confidence>HIGH/MEDIUM/LOW</confidence> <evidence>Code references or documentation</evidence> ``` Add anti-patterns: ``` ## NEVER DO - Never guess without searching first - Never provide code without testing syntax - Never skip reading files you're asked about ``` </example_review> <advanced_patterns> **Additional Patterns to Check** **Parallel Execution Requirements** For tasks requiring thoroughness, does the prompt specify minimum parallel tool usage? ``` Minimum parallel calls by task type: - Simple lookup: 2+ tools - Code search: 3+ tools - Research: 4+ tools Cross-validate results. If tools disagree, investigate. ``` **Delegation Structure** When delegating to other agents, does the prompt require structured handoff? ``` Delegation prompts MUST include: 1. TASK: What specifically needs done 2. EXPECTED OUTCOME: What success looks like 3. MUST DO: Non-negotiable requirements 4. MUST NOT DO: Explicit prohibitions 5. EXIT CRITERIA: How to know it's done ``` **Tool Cost Awareness** Does the prompt guide efficient tool selection? ``` Tool allocation: - FREE: grep/glob/read (use liberally) - CHEAP: explore agent (use for unknown territory) - EXPENSIVE: oracle agent (reserve for complex decisions) Start FREE, escalate only when needed. ``` **Confidence Calibration** Does the prompt require confidence assessment? ``` <confidence> HIGH: Found definitive answer with evidence MEDIUM: Found likely answer, some uncertainty LOW: Best guess, recommend verification </confidence> If LOW, state what additional information would raise confidence. ``` </advanced_patterns> <quick_checklist> **Quick Review Checklist** Before an agent prompt ships, verify: - [ ] **Classification**: Does it categorize requests before acting? - [ ] **Phases**: Are there explicit stages with exit criteria? - [ ] **First action**: Is step 1 concrete and specific? - [ ] **Output format**: Is structure required, not suggested? - [ ] **NEVER DO**: Are common failure modes explicitly prohibited? - [ ] **Escalation**: Does it know when to stop and ask? - [ ] **Tools**: Are permissions explicit and minimal? If more than 2 boxes unchecked, the prompt needs work. </quick_checklist>
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