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Postel

by app.postel
OverviewDiscussionsAdmin

Suggest post rewrite

refine-post

Suggest refined content for an existing post using AI and specific instructions. Does not save changes. Uses 1 AI credit (Lite mode with a daily cap when credits run out).

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": {
      "postId": "<postId>",
      "instructions": "<instructions>"
    },
    "name": "refine-post"
  }
}

Input Schema

NameRequiredDescriptionDefault
postIdYesThe post ID to refine
instructionsYesInstructions for how to refine the post (e.g., 'make it more casual', 'add a call to action')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior5/5

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

Adds context annotations cannot express: the result is non-persistent ("Does not save changes"), it costs 1 AI credit, and there is a degraded Lite mode with a daily cap once credits are exhausted. That cost/fallback/non-persistence disclosure is exactly the behavioral detail an agent needs before calling an open-world AI tool.

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, zero filler, with the core action stated first and the two caveats (no save, credit cost) immediately after. Nothing repeats the name or title.

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 2-parameter tool with annotations present, the description covers action, side effects, and cost. The one gap is that no output schema exists and the description never says what is returned (suggested text inline vs. a job/id), leaving the agent to discover the response shape.

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% and both parameters are documented in-schema with an example for instructions, so the schema carries the load. The description only alludes to "specific instructions" and adds no syntax, length, or formatting guidance beyond that.

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 ("Suggest refined content for an existing post") plus the mechanism (AI + specific instructions), which is meaningfully different from generate-post (new content) and update-post (persists changes). It does not name the sibling it replaces, so the differentiation is inferential rather than explicit.

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?

"Does not save changes" implies the agent should follow up with update-post to persist, but the alternative is never named and there is no explicit guidance on when to prefer this over generate-post or update-post. Usage is implied rather than stated.

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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