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list_drafts

Read-onlyIdempotent

List up to 50 draft post variants awaiting review (status draft or pending_review), newest first — including AI-generated drafts from generate_posts — with platform, caption, hashtags, tone and source.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds genuinely useful behavior beyond that: a hard cap of 50 results, newest-first ordering, the status filter, and the fields returned, which tells the agent exactly what shape of result to expect.

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?

A single sentence, front-loaded with the result cap and resource, then the filter, ordering and payload. No redundant restatement of the title or annotations.

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 input parameters and no output schema, the description bears the whole burden and mostly discharges it by specifying scope, cap, ordering and returned fields. The only gap is what happens beyond the 50-item ceiling (no pagination or cursor mention), which an agent calling the tool might want to know.

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?

The tool takes zero parameters, so there is nothing to mis-specify and the schema cannot carry semantics. The description still adds value by enumerating the returned fields (platform, caption, hashtags, tone, source), which orients the agent despite the absence of any input.

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?

States a specific verb (List) and a precise resource (draft post variants), and narrows the scope with the exact statuses (draft or pending_review) plus sort order. This distinguishes it cleanly from list_posts, review_drafts and generate_posts without opening any schema.

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?

The description implies when this applies by naming the statuses it covers and noting the drafts come 'from generate_posts', which hints at the generate -> list -> review flow. However it never explicitly says when to use this instead of siblings like list_posts or review_drafts, so routing is left to inference.

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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