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Glama

VarynForge

by com.varynforge

Expand idea

expand_idea

Score a raw article idea against the project's niche without writing anything to the plan. Returns a title, angle, search intent, related queries, a coarse demand estimate, and a 0-100 niche-fit score. Pass the returned fields to accept_idea to commit the idea as a brief-ready suggestion.

Input Schema

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

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",
-  "ideaText"
-]New value: +[
+  "projectId",
+  "ideaText",
+  "context"
+]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

The description adds meaningful side-effect context by stating 'without writing anything to the plan', which is valuable beyond the annotations. It also discloses the exact output fields returned. Since readOnlyHint is false, the description narrows the side-effect profile to plan writes, but does not fully clarify whether any other persistence or logging occurs.

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 three sentences long, with every sentence earning its place: the first states the core action and side-effect boundary, the second enumerates outputs, and the third gives the follow-up workflow. It is front-loaded and free of fluff or redundant restatements 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?

Given there is no output schema, the description appropriately lists the returned fields, which is essential for an agent to use the result. It also explains the no-write behavior and the relationship to accept_idea. It does not specify formats for the 'coarse demand estimate' or 'search intent' values, but the overall picture is sufficient for calling this tool correctly.

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 only 33%, so the description must compensate. It partially does by referring to 'raw article idea' and 'project's niche', which map to ideaText and projectId, but it never names the parameters explicitly and says nothing about the required context param. The context schema description helps, but the overall parameter guidance remains incomplete.

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 uses a specific verb ('Score') with a clear resource ('a raw article idea') and scope ('against the project's niche'). It also explicitly states the tool does not write to the plan, and the returned fields are named. This distinguishes it from accept_idea, which commits the idea, and from other sibling tools.

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

Usage Guidelines4/5

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

The description gives a clear workflow: use this tool to score an idea without writing, then pass the returned fields to accept_idea to commit it. This provides a useful sequencing cue and names the relevant alternative. It does not explicitly discuss when-not-to-use or other alternatives like check_idea, but the context is clear enough for selection.

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