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agy_search_skills

Search installed skill names and content to locate the right skill for your task. Retrieve matching results with name and snippet for quick reference.

Instructions

Search across all installed skill names and content.

Return Format

{"results": [{"name": str, "match": str}], "count": int}

Examples

agy_search_skills("python") agy_search_skills("docker")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ctxNo
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3/5.0
Behavior3/5

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

Annotations are entirely empty, so the description carries the full burden of behavioral disclosure. It discloses the search scope (names and content) and the exact return format, and 'search' inherently implies a non-destructive read. However, it doesn't address match semantics, case sensitivity, or result limits. No contradiction with annotations exists since there are none.

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?

The purpose is front-loaded, followed by a compact return-format code block and two clear usage examples. Every sentence earns its place with no filler.

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

Completeness3/5

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

This is a low-complexity search tool with an output schema and the return format also embedded in the description, so results are well covered. However, the opaque ctx parameter is never explained and there is no guidance on when this tool is preferred over its siblings, leaving the definition merely adequate for the core action.

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

Parameters2/5

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

Schema description coverage is 0% and the description mentions neither parameter. 'query' is inferable from the examples and the schema, but 'ctx' (nullable, default null) is entirely unexplained, and the description adds nothing about how the query is matched or what ctx controls.

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 a specific verb (search), resource (installed skills), and scope (names and content), which clearly differentiates it from list_skills (enumerate) and read_skill (load a specific skill). It is clear and specific, though it doesn't explicitly name sibling alternatives within the text.

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

Usage Guidelines2/5

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

No when-to-use guidance, alternatives, or exclusions are given. The examples show syntax but not the conditions under which an agent should choose search over list or read. With 11 sibling tools, the lack of any routing guidance is a notable gap.

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