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symbol_lookup

Find a symbol's definition across multiple languages with signatures, locations, and repo memories to disambiguate before graph or read calls.

Instructions

Resolve a symbol name (or ref/id) to its definition(s) in Rust, TypeScript, Kotlin, C, C++, or Python — exact or fuzzy. Returns candidates with signatures, locations, logical-symbol grouping (cfg variants), and any bound repo memories. Use to disambiguate before a graph or read call. Generated bindings (codegen, ubrn FFI output) are excluded by default; pass include: ["generated"] to see them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
refNo
langNo
limitNo
symbolNo
includeNoWhat to include: `memories` (on by default) and/or `generated` (off by default — opts generated bindings back into the results). Pass `include: []` to suppress memories.
worktreeNoAbsolute path to a linked git worktree you're working in; serves that worktree's branch overlay over the indexed checkout. Omit (or pass an unrelated path) for the indexed checkout.
allow_ambiguousNo
Behavior3/5

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

No annotations are provided, so the description must disclose behavioral traits. It mentions that generated bindings are excluded by default and that memories are included, and that the include parameter controls these. However, it does not explicitly state that the operation is read-only or whether it modifies state, which is a gap given the lack of annotations.

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?

The description is two sentences long, concise, and front-loaded with the core purpose. Every sentence adds value without redundancy or unnecessary detail.

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?

Given the tool has 8 parameters, no output schema, and no annotations, the description covers the main functionality, return format, and key behaviors. It could be improved by explaining more parameters or providing examples, but it is sufficiently complete for an agent to understand its use.

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

Parameters3/5

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

Schema description coverage is low (25%), so the description should compensate. It adds meaning for the include, worktree, and allow_ambiguous parameters, but does not detail other parameters like id, ref, lang, limit, and symbol beyond what the schema provides. The description adds some value but not enough to fully compensate for the low coverage.

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?

The description clearly states the tool resolves symbol names to definitions across multiple languages (Rust, TypeScript, etc.), with exact or fuzzy matching. It specifies the returned information (signatures, locations, groupings, memories) and directly differentiates from siblings by noting it should be used before graph or read calls.

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?

The description explicitly advises to use this tool to disambiguate before graph or read calls, and explains the default exclusion of generated bindings with the include parameter to opt in. While it doesn't explicitly compare to sibling tools like find_callers or trace_callees, the context is clear enough for an agent to understand its primary role.

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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