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recall

Search your codebase knowledge graph for prior art, known failures, and related context using embedding search and graph traversal before making decisions.

Instructions

Broad "what do we know about X" — combines embedding search with graph traversal.

Use this at session start or before making decisions to check for prior art, known failures, and existing context.

Depth controls how far to traverse from matched nodes:

  • 1: direct matches only (fast)

  • 2: matches + their neighbors (default, good balance)

  • 3: two hops out (broader context, slower)

Example: recall(query="federation architecture", depth=2)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesWhat to recall — natural language query
depthNoTraversal depth from matched nodes: 1-3 (default: 1)
Behavior4/5

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

No annotations provided; description compensates with depth parameter details (speed vs. breadth) and an example. Discloses performance trade-offs but not auth or side effects.

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

Conciseness5/5

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

Four tight paragraphs: purpose, usage, parameter details, example. No redundant sentences.

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

Completeness4/5

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

Covers purpose, usage, parameters, and example. Missing return value description but not required for a recall tool.

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?

Schema coverage is 100%; description adds value by explaining depth values (1=fast, 2=balance, 3=slower) and providing an example usage.

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?

Clearly states it combines embedding search with graph traversal for broad knowledge retrieval. Distinguishes from siblings like semantic_search and graph traversal tools.

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

Usage Guidelines4/5

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

Explicitly suggests use at session start or before decisions to check prior art and context. Provides clear context but no exclusions or 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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