Tinplate Edge AI Safety, Security & EU Compliance

tinplate_rag_chunker

Read-onlyIdempotent

Markdown & Code Aware Smart RAG Document Chunker API: Split Markdown into token-budgeted RAG chunks with heading breadcrumbs and intact code/tables. (Endpoint: POST /v1/rag-chunker)

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>",
      "max_tokens": "<max_tokens>"
    },
    "name": "tinplate_rag_chunker"
  }
}

Input Schema

Name	Required	Description
`text`	Yes	Parameter 'text' (e.g. "# Gateway Manual\n\n## Authentication\nPass your proxy secret h")
`max_tokens`	Yes	Numeric parameter 'max_tokens' (e.g. 128)
`overlap_tokens`	No	Numeric parameter 'overlap_tokens' (e.g. 16)
`prepend_breadcrumbs`	No	Boolean flag 'prepend_breadcrumbs' (default: true)

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 15, 2026

TDQS

B3.4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and closed-world, so the safety profile is covered. The description adds real behavioral content beyond them: chunks respect a token budget, headings are carried as breadcrumbs, and code blocks/tables are kept intact rather than split. It stops short of describing edge cases such as a single code block exceeding max_tokens or error behavior.

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?

A single front-loaded sentence conveys the core behavior, with the endpoint appended compactly. The leading 'Markdown & Code Aware Smart RAG Document Chunker API' restates the annotation title, which is slightly redundant but not wasteful enough to penalize heavily.

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

Completeness3/5

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

For a four-parameter, read-only tool with full schema coverage this is mostly adequate. However, with no output schema, the description never says what is returned (a list of chunk strings? objects with breadcrumbs?), leaving the caller to guess 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 description coverage is 100%, so the baseline is 3. The description reinforces that max_tokens is a token budget and that breadcrumbs relate to headings, but it adds nothing about overlap_tokens or the breadcrumb format beyond what the schema already states.

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?

The description names a specific verb and resource: split Markdown into token-budgeted RAG chunks. Qualifiers like 'heading breadcrumbs' and 'intact code/tables' make the behavior distinct from a generic text splitter and implicitly from the sibling tinplate_tabular_rag_cleaner (tabular), but no sibling is named explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to choose this over the tabular cleaner or other tools, no prerequisites, and no exclusions. The endpoint path is included, but that is transport detail rather than usage 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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