FeedSquad

Adapt for Platform

adapt_for_platform

Read-onlyIdempotent

Takes one draft and returns a platform-tuned version for each requested platform (LinkedIn, X, Threads). Keeps the author's wording and applies per-platform constraints (length, link handling, thread splitting) and the user's brand voice. Adds no question, call to action or hashtag the draft did not have. Each version carries a lint_verdict from FeedSquad's draft linter. Returns text only: it creates no draft and changes no post. The draft and the brand voice are sent to FeedSquad's model provider. Bluesky and Mastodon publishing isn't available yet: requesting either returns an error.

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": {
      "draft": "<draft>",
      "platforms": "<platforms>"
    },
    "name": "adapt_for_platform"
  }
}

Input Schema

Name	Required	Description
`angle`	No	Optional angle/framing instruction.
`draft`	Yes	The source draft text to adapt (max 5000 chars).
`platforms`	Yes	One or more target platforms. bluesky and mastodon are accepted for compatibility but return an error: publishing to them isn't available yet.

Output Schema

Name	Required	Description	Default
`kind`	Yes
`adaptations`	Yes
`source_chars`	Yes
`brand_voice_applied`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 6, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Beyond the annotations, the description discloses per-platform constraints, preservation of the author's wording and brand voice, a no-added-content rule, lint_verdict output, external model-provider data flow, and the Bluesky/Mastodon unsupported-platform error. These details are consistent with readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false.

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 action and return behavior, then adds constraints, side-effect guarantees, privacy context, and platform limitations. It is dense but largely purposeful, with only minor repetition of the Bluesky/Mastodon limitation already present in the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the annotations, full schema coverage, and an output schema, the description is complete enough for correct invocation. It covers side effects, external data transmission, platform constraints, unsupported inputs, and the shape of the returned text.

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%, so the schema already documents draft, platforms, and angle. The description adds useful platform behavior and reiterates the Bluesky/Mastodon limitation, but it does not explain the optional angle parameter beyond what the schema provides.

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 states a specific verb and resource: it takes one draft and returns a platform-tuned version for each requested platform. It clearly distinguishes itself from sibling mutation tools by saying it returns text only, creates no draft, and changes no post.

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?

The description makes the usage context clear: adapt an existing draft for one or more platforms, with no draft creation or post mutation. It does not explicitly name alternative sibling tools, but the text-only/no-mutation framing gives an agent enough context to avoid using create_post or update_post instead.

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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