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by ink.octopost
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Split long text into a thread

split_thread
Read-onlyIdempotent

Split long text into thread parts that fit every network you name, breaking at paragraphs, then sentences, then words. Counts the way each network does (X: links are 23, emoji 2; Bluesky: graphemes). Nothing is saved or posted. Pass the result straight to create_post / schedule_post / queue_post as content + segments.

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": {
      "text": "<text>",
      "platforms": "<platforms>"
    },
    "name": "split_thread"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesThe full text to split.
numberingNoAdd " 1/N" to the end of each part. Default false.
platformsYesNetworks the thread will go to. Every part fits all of them.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description reinforces this with 'Nothing is saved or posted.' It adds real behavioral detail beyond annotations: break precedence (paragraphs, then sentences, then words) and platform-specific counting rules (X links as 23, emoji as 2; Bluesky graphemes). It stops short of describing the exact returned structure beyond the hints 'content + segments.'

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 sentences, front-loaded with the purpose, then the algorithm, then the constraint and handoff. Every sentence carries distinct information with no restatement of 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?

With no output schema, the description does enough by naming the destination fields (content + segments) and the splitting rules. Minor gap: it doesn't say what happens when a single word exceeds a network limit, nor the exact shape of the returned array.

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 baseline is 3. The description echoes the platforms parameter's semantics ('fit every network you name') and adds counting behavior, but never mentions the 'numbering' parameter or its effect, leaving that entirely to the schema.

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?

States a specific verb and resource ('Split long text into thread parts') plus the fitting constraint ('that fit every network you name'). No sibling tool does splitting, and the description makes the transformation and its output clear at a glance.

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 explicit downstream routing: 'Pass the result straight to create_post / schedule_post / queue_post as content + segments.' It doesn't state an exclusion or a threshold case, but for a dedicated utility with no competing sibling, the usage context is unambiguous.

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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