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Glama

VarynForge

Update article status

update_article_status
Destructive

Move an article through the production pipeline. Statuses: planned, generating_brief, brief_ready, drafting, draft_ready, reviewing, ready_to_publish, published. For the published transition use mark_article_published instead — it records the live URL, which Search Console outcome tracking keys off; setting status to published here records no URL. When the article is scheduled to go live later (CMS/external scheduler), pass scheduledFor with the planned date — it shows in the app and holds the "stalled at ready_to_publish" flag until the schedule lapses; do NOT call mark_article_published before the URL is live, publish auto-detect attests it (and pings IndexNow) when it actually appears.

Input Schema

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

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: -[
      -  "id",
      -  "status"
      -]New value: +[
      +  "id",
      +  "status",
      +  "context"
      +]
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already mark this as destructive and non-read-only, and the description adds behavioral context: setting status to published here records no URL, scheduledFor holds the stalled-at-ready_to_publish flag, and publish auto-detect attests the live URL and pings IndexNow. It does not contradict the annotations and provides meaningful side-effect detail.

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 description is dense but front-loaded with the core purpose, then covers edge-case transitions and scheduling. It earns its length because each detail prevents a costly wrong invocation, though it could be tightened slightly.

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 mutation tool with no output schema, the description covers the critical decision points: which sibling to use, what happens with scheduledFor, and what the published status lacks. It does not describe the return value or error behavior, but those are less essential given the rich operational guidance.

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 20%, so the description bears a heavy burden for parameter meaning. It substantially clarifies status and scheduledFor semantics, but does not add meaning for id, context, or lastActor beyond what the schema enum/pattern already exposes.

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 action ('Move an article through the production pipeline') and enumerates the full status enum, making the tool's function immediately clear. It also differentiates itself from the sibling mark_article_published by explicitly routing the published transition elsewhere.

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 gives explicit when-to-use and when-not-to-use guidance: use mark_article_published for the published transition, and do NOT call it before the URL is live. It also explains when to pass scheduledFor, clearly separating scheduling behavior from publishing behavior.

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