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knowledge_catalog

List knowledge areas and canonical project documents in Context Grove's read-only, Git-versioned Markdown knowledge base, helping AI agents consult shared guidance before acting.

Instructions

List knowledge areas and canonical project documents. / Liste as áreas de conhecimento e documentos canônicos do projeto.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior2/5

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

With no annotations provided, the description carries the full behavioral burden. 'List' weakly implies a read-only, non-destructive operation and there are zero parameters so mutation risk is low, but nothing is said about what is returned, whether the catalog is scoped to a project, or how items map to the other knowledge tools.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core content is a single short sentence and is front-loaded, which is good. However, the full sentence is repeated verbatim in Portuguese, doubling the length without adding information for most agents; the structure is tidy but the duplication does not earn its place for a general audience.

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?

For a zero-param, no-output-schema listing tool the description is minimally adequate: you know it lists knowledge areas and canonical documents. But with no annotations and no output schema, it is the only source of information about return shape and role within the four-tool knowledge set, and it does not cover either.

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 input schema defines zero parameters, so the baseline of 4 applies. There are no parameter semantics to explain, and the description does not misrepresent any.

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 names a specific verb ('List') and two concrete resources ('knowledge areas and canonical project documents'), which is clear enough that an agent understands this is a catalog/overview tool without opening a schema. It stops short of explicitly differentiating itself from knowledge_search or knowledge_read, but the 'list/catalog' framing is distinguishable.

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?

There is no statement of when to use this tool versus its siblings (knowledge_search, knowledge_read, knowledge_health). Usage is only inferable from the word 'List'; no conditions, prerequisites, or exclusions are given for a toolset with four knowledge tools competing for selection.

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