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get_vision_docs

Read-only

Retrieve design documents like PRDs and CLAUDE.md files to understand code intent and verify implementation against original specifications.

Instructions

Get the documented intent — CLAUDE.md files, PRDs, roadmaps, skill specs — to understand WHY code exists, not just what it does.

CALL THIS WHEN: • You're implementing a feature and need to check if a PRD or spec exists for it • You want to understand the original design intent behind existing code • You need to verify your implementation matches documented requirements • You're reviewing code and want to check it against the documented vision

RETURNS: All vision documents grouped by type (claude_md, prd, skill, roadmap), with each spec's title, section ID, and implementation status showing which functions implement each spec.

EXAMPLES: • "Is there a PRD for the notification system?" • "What does the CLAUDE.md say about the auth module?" • "What specs exist for the slack integration?" • "Which specs are already implemented vs still pending?"

WHY NOT JUST READ FILES: Vision docs are scattered across CLAUDE.md files, PRDs, and roadmaps in different directories. This aggregates them all AND cross-references against actual implementations so you can see spec-to-code alignment in one call.

TIER: Pharaoh Pro — free tier receives a preview. Summarize what the preview reveals, explain what full data would show for this task, then include the upgrade link.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare readOnlyHint=true. Description adds significant behavioral context: aggregation behavior (scattered docs across directories), cross-referencing logic (spec-to-code alignment), and return structure (grouped by type with title/section ID/implementation status). Also discloses tier limitation (Pharaoh Pro preview). Does not mention error conditions or caching behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with clear headers (CALL THIS WHEN, RETURNS, EXAMPLES, WHY NOT JUST READ FILES, TIER). Front-loaded with purpose statement. Length is appropriate given complexity and lack of output schema, though slightly verbose. Every section serves distinct purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, but description fully compensates with RETURNS section detailing grouping logic and field structure. Covers purpose, usage scenarios, return format, alternative comparison, and commercial constraints (Pro tier). Complete for a metadata/aggregation tool with good annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Zero parameters present. Per rubric, 0 params = baseline 4. The EXAMPLES section provides calling patterns ('Is there a PRD for...', 'What does the CLAUDE.md say...') which help clarify usage without parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with specific verb 'Get' and clearly identifies resource as 'documented intent — CLAUDE.md files, PRDs, roadmaps, skill specs'. Distinguishes value proposition (understand WHY code exists) from siblings like get_codebase_map or get_pharaoh_docs. The 'WHY NOT JUST READ FILES' section explicitly differentiates from alternative approaches.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Contains explicit 'CALL THIS WHEN:' section with four specific scenarios (implementing features, understanding design intent, verifying requirements, code review). Includes concrete EXAMPLES with four natural language queries. The 'WHY NOT JUST READ FILES' provides clear selection guidance against direct file reading alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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