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Sendhour

by com.sendhour
OverviewDiscussionsAdmin

Create a draft for review

create_draft

Create a draft for one account, which waits in Sendhour until the user reviews and confirms it. Use it when the user wants to check a post before it is scheduled. Returns a review_url to give the user.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "account_id": "<account_id>"
    },
    "name": "create_draft"
  }
}

Input Schema

NameRequiredDescriptionDefault
kindNoTikTok drafts only (required): video (exactly one video) or photo (1-35 photos).
titleNoTikTok photo posts: title up to 90 characters. YouTube: video title.
threadNoX only: more posts after the caption, posted as a thread
captionNoPost text
is_aigcNoTikTok: suggest the AI-generated content label
link_urlNoLinkedIn only: share this https link as a card
media_idsNoMedia from upload_media_from_url, in order
post_typeNoInstagram only
account_idYesAccount from list_accounts
link_titleNoLinkedIn only: the link card title
visibilityNoYouTube only
external_refNoYour own identifier, returned with the post
scheduled_atNoSuggested ISO 8601 time; the user can change it when confirming
auto_add_musicNoTikTok photo posts: suggest letting TikTok add music

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare a non-destructive, non-open-world write, and the description adds genuinely new behavior: the item is held pending user confirmation before anything is scheduled. It also discloses the return value ("Returns a review_url to give the user"), which matters since there is no output schema. Missing details like per-account auth or draft expiry keep it from a 5.

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?

Three short sentences, front-loaded with the action and its key behavioral distinction, then the when-to-use condition, then the return value. No sentence is redundant with the others.

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 14-parameter multi-platform creation tool, the description covers what an agent most needs: the review-gated lifecycle and the review_url to surface to the user. With no output schema, a bit more on what the returned draft object contains (id, status) would make it 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% across all 14 parameters, so the enum values and per-platform fields (kind, thread, link_url, visibility, etc.) are already fully documented in the schema. The description adds no parameter-level meaning beyond that, which is the baseline case for complete schema coverage.

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 states a specific verb and resource ("Create a draft for one account") and adds the distinguishing trait that the draft waits in Sendhour for review rather than publishing. It implicitly separates itself from schedule_post, though it never names that sibling, so the differentiation is left partly to inference.

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?

"Use it when the user wants to check a post before it is scheduled" gives a clear triggering condition that maps to a real user intent. It stops short of naming the alternative tool (schedule_post) or stating when a draft is the wrong choice, so there is no explicit exclusion.

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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