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MelMayssonOwen

TimeToPost MCP server

Source ingest status

get_source_status
Read-onlyIdempotent

Poll a source ingest by ID to get its status, evidence brief, angle plan, extraction results, and pending drafts. Identifies drafts that require fact-checking before approval.

Instructions

Poll one source ingest by id (from create_posts_from_source). Returns status (QUEUED → FETCHING → BRIEFING → PLANNING → DRAFTING → READY, or EMPTY/FAILED), the evidence-backed brief, the angle plan, the per-item extraction result ("thin" = that page had under 200 words of real text and was excluded rather than hallucinated from), and the PENDING drafts it produced. A draft with needsFactCheck=true could not be fully verified against the source — tell the human before they approve it. CAPABILITY: read — side-effect-free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ingestIdYesIngest id returned by create_posts_from_source
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds substantial behavioral context: it is 'side-effect-free', explains the 'thin' extraction exclusion (under 200 words, excluded rather than hallucinated), and warns that needsFactCheck=true drafts require human approval before publishing. These go well beyond the annotations.

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 sentences, front-loaded with the core purpose. It uses compact notation (status arrows, quoted 'thin') to convey a rich return payload and two important caveats. Every sentence earns its place; no redundant or filler content.

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?

Since there is no output schema, the description must explain return values, and it does comprehensively: the status chain, evidence-backed brief, angle plan, per-item extraction result, pending drafts, and the fact-check flag. For a single-param polling tool, this is fully complete.

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% for the single parameter ingestId, and the schema already states 'Ingest id returned by create_posts_from_source'. The description merely echoes this provenance without adding new parameter syntax, format, or edge-case details. Baseline 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 opens with a specific verb and resource: 'Poll one source ingest by id'. It clearly states the ingest originates from create_posts_from_source, and enumerates the full return payload (status, brief, angle plan, extraction results, pending drafts). This distinguishes it from sibling tools like get_post or list_sources.

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 indicates when to use the tool: after create_posts_from_source returns an ingest id. It provides clear context for polling but does not explicitly list alternatives or when-not-to-use scenarios. This is a minor gap, so 4 rather than 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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