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dantalan

baatjie-mcp-server

by dantalan

Schedule a Signal Post

baatjie_schedule_signal

Schedule social posts and ads across platforms, automatically tagging angel windows at 08:17, 11:11, 13:13, and 22:22.

Instructions

Queue a post or ad for broadcast across platforms, with angel-window awareness.

If the scheduled time matches one of the reserved windows (08:17, 11:11, 13:13, 22:22) the angel label is set automatically and reported back. Times outside those windows are accepted without complaint — the label is simply null.

Args:

  • brand_id (string): Brand key, e.g. 'locare', 'dantalan'

  • brand_name (string): Display name

  • caption (string): Post body

  • platforms (string[]): Target platforms, e.g. ['linkedin','x','instagram']

  • scheduled_date (string): YYYY-MM-DD

  • scheduled_time (string): HH:MM (24h)

  • is_ad (boolean): Whether this is a paid ad (default: false)

  • is_master (boolean): Master/primary signal for the slot (default: false)

  • media (string, optional): Media URL or reference

  • item_type (string, optional): Free-form classification

  • user_id (string, uuid): Owning sigscheCore profile id

  • actor (string): Who is scheduling, for the audit trail

  • response_format ('markdown' | 'json'): Output format

Returns: { "ok": true, "item": {...}, "angel_label": string | null, "audit_logged": boolean }

Examples:

  • Launch post -> brand_id='locare', scheduled_date='2026-08-08', scheduled_time='13:13', platforms=['linkedin','x']

  • Evening story -> scheduled_time='22:22', platforms=['instagram']

Error Handling:

  • Invalid time format is rejected before the write

  • A user_id with no matching profile returns a foreign key explanation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actorNoWho is performing this write, recorded in tanOS audit_log (e.g. 'baatjie', 'marius-ai', 'deon-ai')mcp
is_adNo
mediaNo
captionYesPost body
user_idYesOwning sigscheCore profile id
brand_idYesBrand key
is_masterNo
item_typeNo
platformsYesTarget platforms
brand_nameYesBrand display name
scheduled_dateYes
scheduled_timeYes
response_formatNoOutput format: 'markdown' for human-readable, 'json' for machine-readablemarkdown
Behavior5/5

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

Beyond the annotations (which only indicate non-read-only, non-idempotent, non-destructive), the description discloses the angel-window auto-labeling behavior, acceptance of non-window times, audit logging, return shape, and pre-write validation. This adds substantial behavioral context that annotations alone cannot convey.

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?

The description is front-loaded with the core purpose and uses clear sections (Args, Returns, Examples, Error Handling) that make scanning easy. It is slightly longer than necessary because the Args list largely mirrors the input schema, but every section contributes practical context.

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 13-parameter write tool with no output schema, the description covers the key bases: parameter list, return shape, examples, and error cases. It lacks detail on the exact contents of the returned 'item' object and the semantics of is_master/item_type, but overall it is sufficiently complete for correct use.

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?

Schema description coverage is 54%, and the description compensates by documenting every parameter with concrete examples (e.g., brand_id 'locare', scheduled_time '13:13') and clarifying defaults for is_ad/is_master. It adds value beyond the schema, though some params like media and item_type remain terse.

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 ('Queue') and resource ('post or ad'), plus the distinguishing scope ('for broadcast across platforms, with angel-window awareness'). This clearly differentiates the tool from siblings like baatjie_signal_queue or generic baatjie_insert/update.

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 strongly implies its use for scheduling post/ad broadcasts and includes illustrative examples, but it never explicitly contrasts with alternatives or states when not to use it. The primary use is clear, yet explicit when-vs-alternatives guidance is absent.

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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