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Glama

VarynForge

by com.varynforge

List competitors

list_competitors
Read-only

List companies for a project — marked competitors (important / default / ignored) and SERP-discovered companies (unmarked). Sorted important → default → unmarked → ignored, then by domain. Pass importance to filter to one bucket. Capped at 100.

Input Schema

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

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

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only provide readOnlyHint=true, so the description carries the burden of explaining behavior. It adds the exact sort order, the inclusion of unmarked SERP-discovered companies, and the 100-result cap. These are meaningful behavioral details beyond the annotation.

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 four short sentences with no filler. Each sentence contributes a distinct fact: scope, sort order, filtering mechanism, and result cap. The core purpose is front-loaded.

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?

For a read-only list operation with a single filter, the description covers the essential behavioral context: what is listed, the ordering, the filtering option, and the maximum result count. There is no output schema, and the description does not describe the return shape, but this is a minor gap for a list tool.

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 low at 25%, and the description partially compensates by explaining the `importance` buckets and the result cap. However, it does not add semantics for `projectId` or `context`, relying partly on the schema and self-evidence. The added value is real but 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 clearly states the verb ('List'), the resource ('companies for a project'), and distinguishes between marked competitors and SERP-discovered unmarked companies. The sorting detail also differentiates it from generic list tools like list_organizations and from get_competitor_detail.

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 provides clear context for when to use the tool: listing a project's competitors, including unmarked ones. It also gives a concrete conditional usage hint ('Pass `importance` to filter to one bucket'), though it does not explicitly name sibling alternatives or state when not to use it.

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