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Agent Wikis

by io.github.tonbistudio
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Search wikis

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Read-onlyIdempotent

Find the best-matching PAGES for a query, ranked by how many of your query terms each page covers. Searches one wiki if wiki is given, otherwise every active wiki. Each result has its wiki, path, matched terms, and a short snippet for orientation — then read_document the page to get the answer. Returns a confident flag: if false, the wiki(s) likely lack this — fall back to web search.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search"
  }
}

Input Schema

NameRequiredDescriptionDefault
wikiNoOptional wiki slug to restrict the search. Omit to search all wikis.
queryYesNatural-language or keyword query.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds substantial context beyond them: the term-coverage ranking model, the all-active-wikis default scope, the result fields (wiki, path, matched terms, snippet), and the meaning of the `confident` flag with a fallback action. Since there is no output schema, disclosing the return shape here is genuinely load-bearing.

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?

Three sentences, front-loaded with what the tool returns and how it ranks, then scope, then the follow-up action. Every sentence carries information an agent needs to decide and act.

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?

For a two-parameter search tool with no output schema, the description covers scope, ranking, return fields, and the failure/fallback condition. An agent has everything needed to call it and interpret the response without additional documentation.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning about how `query` is interpreted (term coverage across pages) rather than treating it as an opaque string. The `wiki` semantics largely restate the schema's own 'Omit to search all wikis' wording, so it stops short of a 5.

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 a specific verb and resource ('Find the best-matching PAGES for a query') plus the ranking rule ('ranked by how many of your query terms each page covers'). This clearly separates it from read_document (which fetches a page) and list_wikis (which enumerates wikis).

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?

Gives explicit scope behavior ('Searches one wiki if `wiki` is given, otherwise every active wiki') and routes the agent forward to read_document for the actual answer. It also defines a negative case: when `confident` is false, fall back to web search, which is an explicit when-not-to-use signal.

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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