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cos_graph_resolve

Read-onlyIdempotent

Resolve natural-language queries, paths, or partial IDs to canonical UIDs. Use before other graph operations when the exact UID is unknown.

Instructions

Resolve a natural-language label, path, or partial uid to canonical uids.

Use this BEFORE other cos_graph_* tools when you don't know the exact uid. Tries: direct uid → path/qualname → FTS5 full-text → LIKE fallback.

UID scheme: code:file: · code:function::: · code:class::: code:method:::. · code:module: doc:file: · doc:heading:#: · folder:

Args: q: Natural language ("the dispatcher function"), label ("ClaudeSDKDispatcher"), path ("adapters/claude/sdk_dispatcher.py"), or qualname ("Class.method"). kinds: Comma-separated kind filter (e.g. "function,method,class"). Empty = all. top: Max results (default 10).

Returns: JSON envelope with results (ranked list of {uid, kind, label, …}) and strategy (which resolution path matched).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYes
topNo
kindsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

While annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, the description enriches behavioral understanding by disclosing the exact fallback resolution sequence (direct uid → path/qualname → FTS5 → LIKE) and the return envelope with a 'strategy' field, which is beyond structured 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 well-structured with sections for purpose, usage, UID scheme, args, and return value. Every sentence contributes necessary information—no filler—while the front-loaded first line immediately conveys the tool's function.

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?

Given the tool's complexity (multiple UID formats, fuzzy resolution) and the absence of parameter descriptions in the schema, the description is remarkably complete. It covers the UID scheme, resolution order, all arguments, and return format, leaving no critical gaps for an agent to invoke it correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so the description fully compensates by explaining each parameter's meaning and valid inputs. It details 'q' as natural language, label, path, or qualname; 'kinds' as a comma-separated filter; and 'top' with max results and default. This is essential given the minimal schema metadata.

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 opens with a specific verb and resource: 'Resolve a natural-language label, path, or partial uid to canonical uids.' This clearly states the tool's purpose and differentiates it from siblings by positioning it as the UID resolver to use before other cos_graph_* tools.

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?

Explicitly states when to use: 'Use this BEFORE other cos_graph_* tools when you don't know the exact uid.' It also details the resolution strategy order, adding practical guidance on how the tool handles different query types.

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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