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Glama

VarynForge

by com.varynforge

Get project overview

get_project_overview
Read-only

Get the at-a-glance read on a project — niche summary, keyword stats, nextActions (the ranked queue of what to do next in this project — offer its first entry when the operator asks "what now?"), and topPriorities: the ranked queue of article suggestions (best first — priorityScore desc; radar-born suggestions carry no score until briefed and rank oldest-first below scored ones; source tells you why score/cluster may be null). Entries already at ready_to_publish or published are done, not next — "do the next piece" = the first entry whose status still needs work (planned, brief_ready, drafting, draft_ready, reviewing).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextYesOne sentence: what is the operator trying to achieve right now? Describe their goal, not this tool's purpose.
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"
-]New value: +[
+  "projectId",
+  "context"
+]
  2. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, it discloses ranking semantics, unscored radar-born suggestions, why score/cluster may be null via source, and which statuses count as done. These details meaningfully affect how the result should be interpreted and acted on.

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?

The content is front-loaded and each clause carries operational meaning, but the single dense run-on sentence with nested parentheticals is harder to scan than a bulleted structure would be. It is still appropriately sized for the complexity.

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?

With no output schema, the description thoroughly explains the two ranked queues and the critical status-filtering logic, which are the parts most likely to be misread. Minor gaps remain around the exact shape of 'niche summary' and 'keyword stats', though those are reasonably self-evident.

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?

The description adds no parameter-level guidance; context is already well documented in the schema and projectId is self-explanatory. With 50% schema coverage and no description compensation, a baseline score of 3 is appropriate.

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 identifies the operation ('get') and resource ('project overview') and enumerates the distinctive content: niche summary, keyword stats, nextActions, and topPriorities. This content is specific enough to separate it from sibling getters like get_project.

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?

It gives a concrete trigger ('when the operator asks "what now?"') and explains how to interpret 'do the next piece' using statuses. It does not explicitly contrast itself with alternative tools or state when not to use it, so it stops short of a 5.

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