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skill_search_index

Search skills by case-insensitive substring across names, descriptions, and bodies. Quickly locate relevant skills by topic or keyword.

Instructions

function_purpose: Search skills by case-insensitive substring across name, description, and body.

Description:

  • Performs a simple substring search across the parsed name, description, and body for each skill.

Args:

  • query: str Case-insensitive substring

  • markdown_output: bool If True, return formatted markdown string instead of JSON list (default: False)

Returns:

  • If markdown_output=False: List of dicts with name, description, path

  • If markdown_output=True: formatted markdown string with search results

Usage:

  • Use this to quickly locate relevant skills by topic or keywords.

  • Set markdown_output=True for a more readable format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
markdown_outputNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations are provided, so the description carries the full burden. It discloses case-insensitive substring matching across name/description/body and precisely defines both return modes. The read-only nature is implied but not explicitly stated; no contradictions exist.

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?

Uses labeled sections (function_purpose, Description, Args, Returns, Usage) with front-loaded purpose. However, 'function_purpose' and the first bullet under Description restate the same information, adding minor redundancy.

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?

Captures search semantics, all parameters, return formats, and usage intent. It doesn't discuss when to prefer sibling list/detail tools or limitations like empty results, but overall the description is sufficient for a simple two-parameter search tool.

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 has 0% description coverage, so the description must define parameters. It explains 'query' as a case-insensitive substring and 'markdown_output' as a toggle for markdown vs JSON output, adding meaning beyond the schema's type/default alone.

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?

States 'Search skills by case-insensitive substring across name, description, and body' with a specific verb and target resource. Clearly distinguishes from sibling list/get/create tools by specifying search semantics and searchable fields.

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?

Provides an explicit usage instruction: 'Use this to quickly locate relevant skills by topic or keywords' and advises setting markdown_output=True for readability. Doesn't explicitly mention when to use alternative tools like skill_list_all or skill_get_detail, so it lacks exclusions.

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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