Skip to main content
Glama
kennyrnwilson

knowledge-library-mcp

get_guidance

Find and retrieve guidance documents from the knowledge library by topic. Get the matching markdown file to quickly access relevant instructions and best practices.

Instructions

Return the markdown of 04-guidance/<area>/<topic>.md for the first matching area.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose two behaviors: the return format is raw markdown and the selection is 'first matching area'. However, it doesn't explain how 'area' is resolved from a topic-only parameter, what happens on no match, or whether the operation is read-only. The first-matching behavior is valuable, but the area-matching logic remains opaque.

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?

A single 15-word sentence with zero waste. The path template is front-loaded and the matching behavior is appended at the end; every phrase earns its place.

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 one-parameter read tool with an output schema, the description covers the core return value and location. Remaining gaps are the undefined 'area' resolution mechanism and no-match error behavior, which are material to predicting the tool's output. It is minimally adequate but leaves clear ambiguities.

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 0% and the topic parameter has no schema description, so the description must compensate. It does hint that topic maps to a path/file component via the `<topic>.md` template, but it doesn't clarify topic format or matching behavior. The mention of `<area>` in the path is confusing because area is not a parameter.

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 states a specific verb ('Return') and a specific resource (the markdown file at `04-guidance/<area>/<topic>.md`), making the tool's purpose clear. The path pattern distinguishes it from siblings like get_note, though it doesn't explicitly name any alternative. It is not a tautology, and the 'first matching area' phrase adds behavioral specificity.

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 through the resource pattern: this is the tool for fetching guidance-document markdown by topic. However, the description gives no explicit when-to-use guidance, no exclusions, and doesn't mention alternatives such as search_notes or get_note. An agent must infer when this tool is the right choice.

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

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/kennyrnwilson/knowledge-library-mcp'

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