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Where a draft stands

get_status

Requires a TechFabric engineer's Microsoft sign-in (scope blog.write); an anonymous call is answered with the sign-in challenge. One of your own drafts: its state, what is failing, the last check run, its current Markdown and base_sha (for update_draft), and the preview and editor links (the editor link is yours, for a day: publish from there). When the writer is waiting on a fact only you have, this asks you for it first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe idea id

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
nextYes
noteNo
draftYes
stateYes
titleYes
bylineYes
meaningYes
last_checkYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior5/5

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

This is the description's strongest dimension: it discloses the auth requirement and scope (blog.write), the anonymous-sign-in challenge behavior, the ephemeral nature of the editor link (yours for a day), and that the tool may block to request a fact from the caller. That also explains why readOnlyHint is false for a 'status' tool — it mints a link and can prompt — so the description and annotations are consistent rather than contradictory.

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?

Three dense sentences, each carrying distinct load — auth, returned payload, and the interactive ask. Nothing is padded, though the long compound sentence listing return fields is harder to scan than a short list would be.

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?

Auth, scope, ownership restriction, failure/check-run reporting, base_sha hand-off to update_draft, link expiry, and the interactive-ask behavior are all covered, and an output schema exists to carry exact return shape. An agent has everything needed to call this correctly and interpret the result.

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 coverage is 100% and the single id parameter is documented as 'The idea id'. The description adds only the ownership constraint ('one of your own drafts'), which is mildly useful but mostly reiterates what the schema already conveys. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the resource concretely ('One of your own drafts') and enumerates exactly what is returned: state, failing checks, last check run, Markdown, base_sha, and preview/editor links. It is not a bare restatement of 'get_status'. However it never explicitly distinguishes itself from the similarly named sibling check_draft, so an agent must infer that boundary.

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

Usage Guidelines3/5

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

Scope is implied ('one of your own drafts') and there is one real usage cue — base_sha exists 'for update_draft' and the tool 'asks you for it first' when a fact is needed. But there is no explicit when-not guidance and no differentiation from check_draft or get_page, leaving the agent to guess which status-ish tool to call.

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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