Skip to main content
Glama
nvlang
by nvlang

search

Read-onlyIdempotent

Find documentation entries by name in a Verso site's cross-reference index. Returns ranked matches from canonical and display names, with optional filters for kind and site.

Instructions

Search a Verso documentation site's cross-reference index by name.

Matches entry names and display names (not free text inside pages — use fetch_page to read a page). Results are ranked by match quality and paginated. Read-only.

Args: query: free-text query matched against canonical and user-facing names. site: which configured site (alias from list_sites); omit for the default. kind: optional kind filter — one of the values from list_kinds. limit: maximum results per page, 1-100 (default 20). offset: number of results to skip, for pagination (default 0). response_format: "markdown" (default) or "json".

Returns: markdown: a header ("N matches … showing X-Y") then one bullet per hit ("- [kind] display — url"), plus a hint to re-call with a higher offset. json: {"site","query","kind","total","count","offset","has_more", "next_offset","results":[{"kind","name","display","url",...}]}

Examples: - "Find the simp tactic" -> search(query="simp", kind="tactic") - "Search the FPiL book for monads" -> search(query="monad", site="fpil") - "Next page of results" -> search(query=..., offset=20)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoOptional kind filter from `list_kinds` (e.g. 'tactic', 'section', 'option').
siteNoWhich configured Verso site to use — an alias from `list_sites`. Omit to use the default site.
limitNoMaximum results per page.
queryYesFree-text query, matched against canonical and display names (e.g. 'simp', 'Nat.add', 'monad').
offsetNoNumber of results to skip, for pagination.
response_formatNo'markdown' (human-readable) or 'json' (structured)markdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Beyond the annotations (readOnlyHint, idempotentHint, etc.), the description discloses that results are 'ranked by match quality and paginated,' and explains the behavior for pagination via offset and the hint to re-call with a higher offset. It also details return formats and what fields are included.

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 clear sections (main description, Args, Returns, Examples). Every sentence contributes useful information, and the use of labeled sections improves readability without unnecessary fluff.

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 (6 parameters, multiple response formats, pagination) and rich schema/annotations, the description fully covers all aspects: what it searches, how to filter, pagination behavior, return formats, and examples. No significant gaps remain.

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

Parameters4/5

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

The schema covers all parameters with descriptions (100% coverage), so the baseline is 3. The description adds value through concrete examples mapping natural language ('Find the simp tactic') to parameter combinations, which helps the agent select correct arguments. However, the Args section itself largely paraphrases the schema.

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 states a specific verb and resource: 'Search a Verso documentation site's cross-reference index by name.' It clearly distinguishes itself from sibling tools by noting that it does not search free text inside pages, for which `fetch_page` is the intended alternative.

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?

The description explicitly gives usage context: 'Matches entry names and display names (not free text inside pages — use `fetch_page` to read a page).' It also references sibling tools `list_sites` and `list_kinds` for valid site and kind values, and provides examples of when to use the tool.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/nvlang/verso-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server