Skip to main content
Glama

supportpages_find_article_gaps

Destructive

Analyzes hosted documentation to find gaps in support articles, returning suggestions for review. Does not apply changes automatically.

Instructions

Run hosted documentation analysis and return a durable operation. Suggestions remain pending for review. Never analyse locally, accept suggestions automatically or generate articles implicitly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceNo
request_idNoUse a new UUID for a new intentional request, and reuse it for recovery. Omitted reuses the saved identical request.
open_when_readyNo
prefer_backgroundNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
resultNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.7

TDQS

C2.9/5.0
Behavior3/5

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

Annotations declare destructiveHint=true and openWorldHint=true, and the description usefully adds that it returns a durable operation handle and that suggestions remain pending for review (i.e., no automatic mutation of content). But it never explains what the 'destructive' behavior actually is or where the durable operation is resolved, leaving the highest-risk aspect of the annotations unexplained.

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

Conciseness4/5

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

Three short sentences with the core action front-loaded and constraints following; there is no padding. The phrasing is terse to the point of being elliptical, but every sentence carries an instruction.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists so return values need not be spelled out, but a destructive, open-world tool with three undocumented parameters and no statement of what is analyzed or what the operation produces is under-specified. The description does not close the gaps the schema and annotations leave open.

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

Parameters2/5

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

Schema coverage is only 25% (just request_id documented); workspace, open_when_ready, and prefer_background have no descriptions anywhere. The description adds nothing about these parameters, so three of four inputs remain opaque and the agent must guess at their meaning and defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states it runs a 'hosted documentation analysis' and returns a durable operation, but never mentions the resource the tool is named for (article gaps) or what kind of analysis it performs. An agent gets the general shape (async hosted analysis producing pending suggestions) but cannot distinguish the specific intent from siblings like suggest_sections or recommend_articles based on the text alone.

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?

The negatives ('never analyse locally, accept suggestions automatically, or generate articles implicitly') imply this is the hosted-analysis path and that output is advisory-only, which is useful routing context. However, no alternative tool is named and no positive trigger ('use when you want to detect coverage gaps in published docs') is given, so the when-to-use condition remains inferred.

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