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ts_search

Retrieve Token Savior tool candidates matching a natural-language query via embedding cosine similarity. Outputs schema or TypeScript signature for each.

Instructions

Find the top-K Token Savior tools most relevant to a natural-language query via embedding cosine similarity. Use when the manifest is in 'tiny' or 'code_mode' profile or you don't know which tool fits. Returns each candidate with its full inputSchema (format='schema') or a one-line TypeScript signature (format='ts') suitable for ts_execute scripts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural-language description of what you need (e.g. 'find dependents of update_user').
top_kNoHow many tool candidates to return (default 5, max 12).
include_schemaNoIf false, drop inputSchema from the response (smaller payload).
formatNo'schema' (default) returns JSONSchema; 'ts' returns a TypeScript signature for Code Mode scripts. Auto-set to 'ts' when profile=code_mode.
Behavior4/5

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

No annotations exist, so description carries full burden. It discloses that results include full inputSchema or TypeScript signature and that format auto-sets in code_mode. It does not mention performance or limitations, but for a search tool this is adequate.

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?

Two sentences: first states purpose and method, second covers usage and result format. Front-loaded, efficient, no redundant words.

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?

With 4 parameters and no output schema, the description explains all parameters, usage context, and output. It lacks mention of error handling or empty results, but is otherwise complete.

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 coverage is 100%, but description adds substantial value: explains query as natural-language, notes defaults (top_k=5, max=12), describes format options and auto-setting. This goes well beyond schema.

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

Purpose4/5

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

The description states the tool finds relevant tools via embedding cosine similarity. It clearly identifies the action (find) and the resource (Token Savior tools). However, it could more explicitly differentiate from other search tools like memory_search or search_codebase, which are siblings.

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 says to use when the manifest is in 'tiny' or 'code_mode' profile or when uncertain which tool fits. It provides context but does not list alternatives or when not to use.

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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