postcopilot_generate_postGenerate a viral Threads post using a fine-tuned AI model. Provide a topic or idea and get a ready-to-post caption. Returns the generated text.
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | AI model to use: 'gpt' (fine-tuned GPT, default) or 'llama' (Together AI Llama) | gpt |
| message | Yes | The topic, idea, or prompt for the Threads post |
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations cover the safety profile (readOnlyHint=true), so the bar is lower. The description usefully clarifies that the tool only generates and returns text rather than publishing to Threads, which disambiguates side-effect expectations beyond what the annotation states. It stops short of disclosing latency, rate limits, or output length.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences with zero filler, front-loading the action and the returned artifact. Nothing is repeated from the name or schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter generative tool with no output schema, the description covers the input expectation and states that the generated text is returned, which is the key behavioral fact an agent needs. It omits any sense of output style, length, or determinism, leaving a small gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both 'message' and the 'gpt'/'llama' enum are fully documented in the schema. The description mentions the model and the topic input but adds no format, length, or style constraints beyond the schema, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: 'Generate a viral Threads post', and adds the mechanism ('fine-tuned AI model') plus the output ('ready-to-post caption'). This clearly separates it from the sibling export/download/read tools, none of which produce text.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It tells the agent what to supply ('Provide a topic or idea') but gives no when-to-use vs. when-not conditions, prerequisites, or alternative tools. Usage is only implied by the input expectation, not by explicit routing guidance.
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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