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nodiom-mcp

Delete Markdown node

nodiom_delete

Delete specific Markdown sections or list items with structural selectors, leaving all other content untouched. Targets exact node for precise edits.

Instructions

Removes the node or section matched by the selector. Use "## Section > li[0]" to delete the first list item. Use "## Section" to delete an entire section including its heading. All other content is untouched.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileYesAbsolute path to the Markdown file.
selectorYesSelector for the node to delete. Example: "## Completed > li[0]", "## Old Section"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It clearly states that delete operations on a selector can remove a list item or an entire section including its heading, and confirms that all other content is untouched. It does not mention whether deletions are irreversible or whether any confirmation is required, but the destructive nature is explicit.

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?

The description is three sentences long, front-loads the core action, and uses examples to illustrate selector syntax efficiently. Every sentence earns its place: the first states the action, the second and third clarify scope with examples and reassurance. No fluff or repetition.

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?

For a two-parameter deletion tool with clear behavioral implications, the description is complete. It explains the selector semantics, the two levels of deletion, and the safety guarantee that other content is untouched. The absence of an output schema is acceptable because the tool's return value is not critical to correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema describes both parameters but with minimal detail. The description adds valuable meaning to the selector parameter by explaining its syntax and providing two concrete examples that cover different scopes of deletion. With only 2 parameters and the selector being the critical one, the description compensates well for the schema's brevity.

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 ('Removes the node or section matched by the selector') and provides concrete examples that distinguish it from siblings like nodiom_append and nodiom_write. It clearly identifies the scope of what is deleted (node vs entire section including heading), which is unambiguous.

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 examples show when to use the tool and what selector syntax to use for different deletion targets. It explicitly says 'All other content is untouched,' which sets expectations about scope. It does not explicitly name alternatives or exclusion conditions, but the examples provide sufficient context for when this tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.