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Generate posts with GBPly AI

generate_posts

Use GBPly's AI to write 1-8 Google posts for a business. Costs 1 credit per post actually created, charged to the workspace. Runs immediately with no approval step. Posts are saved as 'pending review' on the GBPly Posts page and are NOT published. If the workspace lacks credits, nothing is generated. Confirm the post count and credit cost with the user before calling.

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": {
      "business_profile_id": "<business_profile_id>"
    },
    "name": "generate_posts"
  }
}

Input Schema

NameRequiredDescriptionDefault
post_typeNoSTANDARD
post_countNoHow many posts to write (1-8). 1 credit each.
start_dateNoFirst suggested date, YYYY-MM-DD.
cadence_unitNo
instructionsNoOptional guidance on topics or tone.
cadence_numberNo
business_profile_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing credit cost per post billed to the workspace, immediate execution without approval, the failure mode when credits are exhausted, and that output lands as 'pending review' rather than published. This is exactly the side-effect context an agent needs before a non-idempotent write.

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?

Five short sentences, front-loaded with purpose and cost, then side effects, then the confirmation instruction. Every sentence carries distinct information with no filler.

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?

Strong for a mutating generation tool with no output schema: side effects, cost, failure behavior, and result state are all covered. The gap is that it never indicates roughly what a successful call returns (e.g., generated post drafts or identifiers) or how scheduling parameters affect output.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 43%, and the description compensates only for post_count (repeating the 1-8 range and credit cost). It says nothing about post_type variants, how cadence_number and cadence_unit combine, what start_date controls, or what business_profile_id must reference, leaving five parameters semantically thin.

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?

States a specific verb and resource: write 1-8 Google posts for a business using GBPly AI. The 'pending review, NOT published' clause implicitly separates it from the request_create_post/request_publish family, but it never names a sibling, so an agent must still infer routing.

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?

Gives clear pre-call conditions: confirm the post count and credit cost with the user, and know that it executes immediately with no approval step. It offers no explicit when-not or alternative-tool routing against request_create_post or request_create_repeating_post.

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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