resolve-ambiguity

name	resolve-ambiguity
description	Systematic ambiguity resolution through tiered information gathering. Use when facing unclear requirements, unknown context, uncertain implementation choices, or any situation where guessing would be risky.
allowed-tools	["Read","Glob","Grep","WebSearch","WebFetch","AskUserQuestion","Task"]

Resolve ambiguity through a systematic process that prioritizes accurate information over guessing. This skill determines the best source for missing information and retrieves it efficiently.

Core principle: Rather ask than guess. Wrong assumptions waste more time than clarifying questions.

<quick_start> <decision_tree> When you encounter ambiguity, classify it:

1. Technical/Factual - "How does X work?" "What is the correct syntax?" → Likely found in project or online sources → Follow the tiered lookup process

2. Intent/Choice - "Which approach should I use?" "What does the user want?" → Requires user input → Use AskUserQuestion immediately </decision_tree>

<immediate_action> If ambiguity is about user intent or preference: → Skip lookup, go directly to <user_clarification> section

If ambiguity is technical/factual: → Follow <tiered_lookup> process </immediate_action> </quick_start>

<tiered_lookup> For technical/factual ambiguity, check sources in this order. Stop as soon as you find authoritative information.

<tier_1 name="Project Context Files"> Check first - fastest and most relevant

1. Read .claude/workspace-info.toon

   • Contains workspace structure, projects, capabilities, outcomes
   • Shows current focus and IDE configuration

2. Read .claude/project-info.toon

   • Contains project technology, dependencies, entry points
   • Shows repository and IDE details

Task(subagent_type="Explore", model="haiku", prompt="""
Check for context files:
- .claude/workspace-info.toon
- .claude/project-info.toon

If found, extract relevant information about: {specific question}
Return only the relevant fields, not the entire file.
""")

</tier_1>

<tier_2 name="Architectural Files"> Check second - project-specific patterns

Look within current scope for:

• CLAUDE.md - Project instructions and conventions
• README.md - Project overview and setup
• ARCHITECTURE.md or docs/architecture.md - Design decisions
• Configuration files relevant to the question:
  • package.json, tsconfig.json (JavaScript/TypeScript)
  • pyproject.toml, setup.py (Python)
  • Cargo.toml (Rust)
  • .env.example (environment variables)

Glob for architectural files:
- **/CLAUDE.md
- **/README.md
- **/ARCHITECTURE.md
- **/docs/*.md

</tier_2>

<tier_3 name="Documentation via MCP"> Check third - if MCP documentation tools are available

If MCP tools are available for documentation lookup:

• Use mcp__context7__* for library documentation
• Use mcp__firecrawl__* for web documentation
• Use other documentation-specific MCP tools

These provide structured access to official documentation. </tier_3>

<tier_4 name="Web Search Official Sources"> Check fourth - for external APIs, libraries, standards

Use WebSearch and WebFetch for:

• Official documentation sites
• GitHub repositories of libraries
• API reference documentation
• RFC or specification documents

<search_strategy>

1. WebSearch with specific query: "{library/API name} documentation {specific topic} 2024 2025"
2. WebFetch the most authoritative result (official docs preferred)
3. Extract only the relevant information

Prefer sources in this order:

1. Official documentation (*.dev, *.io, readthedocs)
2. GitHub repository README/docs
3. Stack Overflow with high votes (for edge cases) </search_strategy> </tier_4>

<when_to_stop> Stop the tiered lookup when:

• You find authoritative information that resolves the ambiguity
• You've checked all relevant tiers without finding information
• The information found indicates this is actually a choice/intent question

If all tiers exhausted without answer → proceed to <user_clarification> </when_to_stop> </tiered_lookup>

<user_clarification> For intent/choice questions, or when tiered lookup fails, ask the user directly. Never guess when user input is available.

1. **Explain what you need** - Tell the user what information is missing 2. **Explain why you need it** - Describe how the answer affects the outcome 3. **Offer smart choices** - If you can infer likely options, present them 4. **Best practice first** - Order choices with recommended approach at top 5. **Bad ideas last** - If including risky options, put them at the bottom 6. **Always allow custom input** - User can always provide their own answer 7. **When uncertain, don't guess choices** - Better to ask open-ended than offer wrong options

<with_known_choices> When you can confidently identify the options:

AskUserQuestion with structure:
- Question: Clear, specific question explaining context
- Options ordered by preference:
  1. Best practice / Most common / Recommended
  2. Good alternative
  3. Another valid option
  4. Least recommended / Has drawbacks
- Each option includes description explaining implications
- User can always select "Other" for custom input

Question: "Which authentication approach should I implement?"

Options (ordered best → least recommended):

1. JWT with refresh tokens - Industry standard, stateless, works well with APIs
2. Session-based auth - Simple, works well for server-rendered apps
3. OAuth2 only - Good for social login, but adds complexity
4. Basic auth - Simple but less secure, only for internal tools

Each option explains trade-offs so user can make informed choice. </with_known_choices>

<without_known_choices> When you cannot confidently identify the options:

DO NOT GUESS. Ask an open-ended question instead.

AskUserQuestion:
- Question: Explain what you need to know and why
- Options:
  1. A general direction if you have any hint
  2. (Keep options minimal or omit entirely)
- Allow free-form input as primary response method

Instead of guessing configuration options:

Question: "I need to configure the database connection. What database are you using and what are the connection details?"

Options:

1. I'll provide the details - Let me type the configuration

This is better than guessing "PostgreSQL" or "MySQL" when you don't know. </without_known_choices>

<formatting_rules>

1. Single question at a time - Don't overwhelm with multiple questions
2. 2-4 options maximum - More becomes confusing
3. Descriptions are required - Every option needs context
4. No yes/no when options exist - Offer the actual choices instead
5. Acknowledge uncertainty - "I'm not sure which applies, so..." </formatting_rules> </user_clarification>

<ambiguity_categories> Examples: "How do I call this API?" "What's the correct syntax?"

Resolution path:

1. Check project context files
2. Check architectural docs
3. WebSearch official documentation
4. If still unclear → ask user for clarification

**Examples**: "What naming convention?" "Where should this file go?"

Resolution path:

1. Check CLAUDE.md for explicit conventions
2. Check existing code for patterns (Glob + Read)
3. Check README/contributing guide
4. If no clear pattern → ask user preference

**Examples**: "Which feature first?" "Should I also refactor X?"

Resolution path:

1. Skip lookup - this requires user input
2. AskUserQuestion immediately
3. Present inferred options if confident
4. Allow open-ended response if uncertain

**Examples**: "Which version of X?" "What's the API for Y?"

Resolution path:

1. Check package.json/pyproject.toml for versions
2. WebSearch for current documentation
3. WebFetch official docs
4. If version-specific behavior → confirm with user

**Examples**: "What port?" "What environment variables?"

Resolution path:

1. Check .env.example or config files
2. Check project-info.toon
3. Check README for setup instructions
4. If sensitive values → ask user (never guess credentials)

**Examples**: "Monolith or microservices?" "Which pattern to use?"

Resolution path:

1. Check ARCHITECTURE.md or design docs
2. Check workspace-info.toon for project structure
3. This is usually a choice → AskUserQuestion
4. Present trade-offs clearly in options

</ambiguity_categories>

**Detect ambiguity**: Identify what information is missing and classify it: - Technical/Factual → Tier lookup - Intent/Choice → User clarification

<step_2> For technical ambiguity: Execute tiered lookup in order:

1. Project context files (.claude/*.toon)
2. Architectural files (CLAUDE.md, README, docs)
3. MCP documentation tools (if available)
4. WebSearch/WebFetch official sources </step_2>

<step_3> For intent ambiguity or lookup failure: Use AskUserQuestion:

• Explain what's needed and why
• Offer choices ordered by recommendation (if known)
• Don't guess choices if uncertain
• Always allow custom input </step_3>

<step_4> Apply the answer: Use the information to proceed with the task. Document any decisions made for future reference. </step_4>

<success_criteria> Ambiguity is resolved when:

• Information found: Authoritative source confirms the answer
• User clarified: User provided explicit direction
• Documented: Decision is captured for future reference

Signs of good resolution:

• No guessing occurred
• User wasn't asked unnecessary questions
• The answer came from the most appropriate source
• Forward progress is now possible </success_criteria>

<anti_patterns> Wrong: Making assumptions and proceeding without verification Instead: Take 30 seconds to check or ask

**Wrong**: Asking 5 questions before doing anything **Instead**: Ask only what's blocking immediate progress **Wrong**: "How should I proceed?" **Instead**: "Should I use approach A (benefit) or B (benefit)?" **Wrong**: "Should I use the factory pattern or strategy pattern?" **Instead**: Explain the options in plain terms with trade-offs **Wrong**: Silently using a default without mentioning alternatives **Instead**: "I'll use X (the standard approach). Let me know if you'd prefer Y."