Skip to main content
Glama

VarynForge

Get draft status

get_draft_status
Read-only

Re-read an article suggestion's verification state without re-linting: the suggestion's single pipeline status plus, per destination format, the stored draft and the latest gate receipt (verdict, per-check detail, thresholds) from its last lint_draft submission. Free and uncapped — always use this instead of lint_draft to recover a known verdict. Pass format to read one destination including the stored draft text; omit it for the per-destination overview (receipts only, no draft bodies). Status-ownership model: ONE suggestion status drives the pipeline while verdicts are per-destination (N receipts), and status transitions are forward-only — a later flagged submission on one destination never demotes a suggestion another destination already moved to ready_to_publish.

Input Schema

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

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: -[
      -  "suggestionId"
      -]New value: +[
      +  "suggestionId",
      +  "context"
      +]
  2. Added

TDQS

A4.9/5.0
Behavior5/5

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

Although readOnlyHint is already true, the description adds materially beyond annotations: the tool is 'free and uncapped,' it returns per-destination receipts plus a single pipeline status, and it explains the forward-only status-ownership model where one destination's later failure cannot demote another destination's ready_to_publish state. This is non-obvious behavioral context that prevents misinterpretation.

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 dense but every sentence earns its place: the first sentence defines the resource and output shape, the second gives usage priority, the third explains the format parameter, and the fourth clarifies the ownership model. The most important scoping constraint is front-loaded without burying the key information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description must explain the return shape, and it does: pipeline status, per-destination format, stored draft, gate receipt, verdict, per-check detail, and thresholds. Combined with the clear parameter guidance and the readOnlyHint annotation, nothing an agent needs to select and invoke this tool correctly is missing.

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 coverage is only 33%, so the description carries meaningful weight for parameters. It clearly explains format's semantics (include draft text vs. overview-only) and ties suggestionId to 'an article suggestion,' which is inferable but not explicitly spelled out. The context parameter is already described in the schema, so the description adequately compensates overall.

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 opens with a specific verb and resource: 'Re-read an article suggestion's verification state without re-linting.' It clearly differentiates itself from lint_draft by emphasizing it recovers a known verdict rather than performing a fresh lint, so an agent can immediately identify what this tool does and does not do.

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 is explicit about when to use this tool: 'always use this instead of lint_draft to recover a known verdict.' It also gives concrete decision guidance for the format parameter—pass it to include stored draft text, omit it for the overview—which tells the agent exactly how to tailor the call to the operator's goal.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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