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DemandBird

by com.demandbird.app
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draft_post

Use ONLY when the user explicitly asks AI to write, generate, or help compose a post, e.g. 'write me a post about X', 'draft something about Y'. Do NOT use this when the user provides their own content. Uses AI to generate content in the user's voice and the workspace's brand identity (positioning / audience / pillars), then saves it as a draft. PREFER this over writing the post yourself and calling save_draft: it applies the full voice engine.

Input Schema

NameRequiredDescriptionDefault
imagesNoImages, a video, or one PDF to attach. For ANY image beyond a thumbnail, call upload_image FIRST to get a presigned S3 URL, upload via the returned curl command, then pass the s3_key here. Inline `data` is only for tiny images (≤50 KB); `file_path` is dev-only. A PDF posts as a LinkedIn document (a swipeable carousel): LinkedIn only, one per post, never alongside images or video.
promptYesTopic or instructions for what to write
youtubeNoYouTube-specific options. Required platform inputs: a video must be attached via `images` (the upload tool accepts video MIME types). If `title` is omitted, it is derived from the first line of content (truncated to 100 chars).
platformNoTarget platform. Influences tone and length. Instagram needs an image or video on the post: upload one with `upload_image` (or make one with `generate_image`) and pass its s3_key in `images`.
draft_anywayNoSet true to make the writer draft with what it has instead of asking for more context. Use when a previous draft_post call came back with 'Need more to draft this' and the user would rather you just write it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already flag readOnlyHint=false and destructiveHint=false, so the description adds meaningful context: generation runs through the workspace voice engine (positioning/audience/pillars) and persists as a draft, not a published post. It also hints at a 'Need more to draft this' non-success outcome via draft_anyway, though it doesn't cover latency/cost of generation.

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 tight sentences with the gating rule front-loaded and the alternative routing at the end. Minor redundancy between 'PREFER this over...' and the voice-engine justification, but nothing wasted.

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 generative mutation tool with no output schema, it conveys the destination (a saved draft), the voice/brand dependency, and the insufficient-context fallback. The return shape is only partially implied, keeping it short of full completeness.

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 100%, so parameters are already fully documented; the description adds no parameter-level detail beyond what the schema states (prompt is not elaborated on). Baseline 3 applies.

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 and resource — AI-generates post content and saves it as a draft — and explicitly contrasts with the sibling save_draft plus the pivot of writing it yourself.

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?

Gives an explicit trigger ('ONLY when the user explicitly asks AI to write/generate/compose'), an explicit exclusion ('Do NOT use when the user provides their own content'), and names the alternative path (writing it yourself then save_draft).

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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