Split Markdown into heading-aware chunks for search and RAG.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "md_chunk"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full behavioral burden, and it only discloses the chunking strategy (heading-aware). It says nothing about whether chunk size is configurable, how oversized sections are handled, what the return structure looks like, or how non-Markdown or malformed input is treated.
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?
A single twelve-word sentence with no filler, front-loading the action and the key algorithmic trait. Nothing could be removed without losing information.
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 simple pure transform this could be adequate, but with no output schema, no annotations, and an input schema that defines no properties, the agent cannot tell what the request body must contain. The definition leaves the hardest question, how to actually invoke it, unanswered.
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?
Parameter count is zero and the schema is an open object with additionalProperties and no declared properties, so nominally the zero-param baseline would apply. In practice the agent is expected to POST a body yet the description never names a field (source markdown, max chunk size, heading depth), so it adds no meaning about what to send.
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?
"Split Markdown into heading-aware chunks" gives a specific verb (split) and resource (Markdown) plus the distinguishing trait that chunks respect headings. This separates it from the string/codec utilities in the sibling list, though 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
"for search and RAG" implies the downstream use case, which hints at when to reach for it, but there is no explicit when-to-use, when-not-to-use, or alternative named. The agent must infer that this is the tool to pick over a plain text splitter.
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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