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Glama

VarynForge

by com.varynforge

Expand radar topic

expand_radar_topic

Expand one radar topic (by signalObservationId + topicIndex from list_radar_topics) into 3-6 candidate article angles with title, intent, and editorial positioning; each angle is flagged when a near-duplicate already exists in the content plan. Optionally pass customPov for angles from a specific point of view. No writes — pass chosen angles to add_radar_topic.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextYesOne sentence: what is the operator trying to achieve right now? Describe their goal, not this tool's purpose.
customPovNo
projectIdYes
topicIndexYes
signalObservationIdYes

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedInput schema / properties / context
      Added value: +{
+  "description": "One sentence: what is the operator trying to achieve right now? Describe their goal, not this tool's purpose.",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "projectId",
-  "signalObservationId",
-  "topicIndex"
-]New value: +[
+  "projectId",
+  "signalObservationId",
+  "topicIndex",
+  "context"
+]
  2. First observed

TDQS

A4/5.0
Behavior1/5

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

The description states 'No writes', but the annotation readOnlyHint: false indicates the tool is not guaranteed read-only. This is a direct contradiction between the free-text description and the structured annotation, requiring a score of 1 per the rubric. The near-duplicate flagging detail is useful but cannot compensate for the contradiction.

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?

The description is compact and front-loaded: the primary action, resource, and output appear immediately. Every clause adds useful information, and there is no filler or redundant restating of the tool name.

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?

The description covers the tool's inputs, output shape, optional parameter, duplicate-flagging behavior, and handoff to add_radar_topic, which is enough for an agent to call it correctly. It does not detail failure behavior or fully explain projectId/context, but the schema already describes context and the overall usage is clear.

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 description coverage is only 20%, so the description must compensate. It meaningfully explains signalObservationId + topicIndex as the identity of the radar topic from list_radar_topics and clarifies that customPov is optional and controls the point of view. projectId is not described, but it is a conventional required identifier, and the required context parameter has a schema description.

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?

The description states a specific verb (expand), a clear resource (one radar topic), and the concrete output: 3-6 candidate article angles with title, intent, and editorial positioning. It also differentiates the tool from siblings by referencing list_radar_topics as the source and add_radar_topic as the downstream destination.

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?

The description explicitly says 'No writes — pass chosen angles to add_radar_topic', which tells the agent when this tool is not the right final step and routes it to the sibling that follows. It also states that the inputs come from list_radar_topics, giving clear usage context.

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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TDQS

A3.8/5.0
Disambiguation4/5

Most tools target a distinct resource and action, and the descriptions carefully cross-reference close alternatives (e.g., add_article_suggestion vs create_article_suggestion_with_input vs accept_idea). A few brief/read variants like get_article_brief, get_write_handoff, and download_brief_markdown could still be confused despite helpful explanations, so the set is not perfectly unambiguous.

Naming Consistency5/5

Tool names follow a highly consistent verb_noun snake_case pattern throughout: get_*, list_*, create_*, update_*, set_*, add_*, delete_*, start_*, expand_*, etc. Even the less common names like lint_draft and remap_asset are still clear verb_noun constructions.

Tool Count1/5

At 57 tools, this far exceeds the 50+ extreme threshold for a single MCP server. Even for a broad content workflow, the surface is overwhelming and would benefit from consolidation or splitting into focused servers.

Completeness4/5

The tool set covers the full content lifecycle: project setup, research runs, opportunity clustering, suggestion creation, brief generation, drafting, linting, publishing, reporting, and account management. Minor gaps exist—destinations and projects cannot be deleted via MCP, and there is no direct update for article suggestion metadata—but these are workable via the web UI or existing tools.

Resources