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Glama

delete_row

Delete a row from a Markdown table using its version hash and row index, returning a new hash for safe subsequent edits.

Instructions

Delete a row. Requires version hash from read_table.

On success returns ONLY v:{new_hash}. On error returns JSON with "error" and "message" fields.

Args: file_path: Absolute path to the Markdown file. table_index: 0-based table index from list_tables. version: 12-char hex hash from read_table (after "v:"). row_index: 0-based data row index to delete (header row is NOT counted).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
versionYes
file_pathYes
row_indexYes
table_indexYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden, and it does well by specifying success output (`v:{new_hash}`), error output shape, and the requirement for a version hash. It could further disclose permanence/irreversibility or version-conflict behavior, but the provided details are substantive and actionable.

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 compact and well-organized: one-line purpose, two concise behavior notes, then a clean Args list. Every sentence adds necessary information, and the critical success/error format is front-loaded before parameter details.

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 delete operation with no output schema and no annotations, the description covers purpose, prerequisites, all parameter semantics, success response, and error response. An agent has enough information to invoke the tool correctly and interpret the result without guessing.

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

Parameters5/5

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

Schema description coverage is 0%, so the Args block is essential and fully compensates. Each parameter gets meaningful detail: file_path is absolute, table_index is 0-based and sourced from list_tables, version is a 12-char hex hash from read_table, and row_index explicitly excludes the header row. This goes far beyond the raw 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?

The description opens with a specific verb and resource: "Delete a row." It then clarifies the row is in a Markdown file at a given path and table index, which distinguishes it from siblings like delete_column and insert_row. An agent can immediately understand what action this tool performs.

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 provides clear contextual requirements: the caller must supply a version hash from read_table and a table index from list_tables. It does not explicitly name alternatives or state when not to use it, but the prerequisites and operation type make the intended usage obvious.

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