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query_wiki

Ask natural language questions against the Agentic-KB to get cited, synthesized answers from public, private, or all scopes.

Instructions

Ask a natural language question against the KB using the AI WikiQuery engine. Returns a synthesized answer with citations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pinNoPIN required when scope is "private" or "all".
scopeNoContent scope: public (default), private, or allpublic
questionYesThe question to answer using the KB

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the return behavior (synthesized answer with citations), which is useful, but says nothing about permissions, rate limits, or cost. The PIN/scope access requirements are only covered by the schema, not the description.

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 tight sentences, front-loaded with the action and resource and immediately followed by the return shape. No filler words or 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?

For a single-question Q&A tool with full schema coverage, the description covers what it does and what it returns. With no annotations, a brief note that it is a read-only query would have closed the remaining gap, but the tool is otherwise adequately described.

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

Parameters3/5

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

Schema description coverage is 100%, so parameters are fully documented in the schema; the description adds no syntax or format detail beyond it. The baseline of 3 applies when the schema already does the heavy lifting.

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?

States a specific verb (ask a question) and resource (KB) plus the engine, and the phrase 'synthesized answer with citations' implicitly separates it from siblings like search_wiki that return raw documents. It stops short of naming the alternative explicitly, so it is clear but not maximally differentiated.

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

Usage Guidelines3/5

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

Usage is implied: reach for this when you want a synthesized answer rather than retrieved documents, contrasting with search_wiki/read_article. No explicit when-to-use, when-not-to-use, or named alternative is given, so guidance is inferred rather than stated.

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