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proj_export_variant_matrix_csv

Export a component-by-variant CSV matrix showing Fitted, Not Fitted, or Alternate status for every component, so variant data merges cleanly with a BOM in spreadsheet tools.

Instructions

Write the variant fitted/not-fitted matrix to a CSV.

Builds the conventional component-by-variant table: one row per flattened component, one column per variant, each cell Fitted / Not Fitted / Alternate. Unlike proj_list_variants (which lists only per-variant deviations), every component appears, so the file merges cleanly with a BOM in a spreadsheet.

Args: output_path: Destination .csv. Defaults to workspace/variant_matrix.csv. project_path: Optional project path. If None, uses the focused project.

Returns: {"output_path", "component_count", "variant_count"} or an error.

Input Schema

NameRequiredDescriptionDefault
output_pathNo
project_pathNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.1

TDQS

A4.3/5.0
Behavior3/5

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

With no annotations, the description does most of the behavioral work: it identifies the tool as a file-writing export, gives the default destination, and states the return shape or error. However, it does not disclose whether existing files are overwritten, whether directories are created, or any permission/encoding behavior, which matters for a write tool with no annotation coverage.

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 front-loaded with the core action and table definition, followed by the useful sibling contrast, then Args and Returns. The information is organized and no sentence is purely filler.

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?

For a two-parameter CSV export with an output schema, the description is largely complete: it explains the exported matrix, default path, project fallback, and return fields. The main remaining gap is write-safety behavior such as overwrite handling, which is relevant because no annotations are provided.

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 description must carry parameter meaning, and it does: output_path is a destination .csv with a specific default, and project_path is optional and falls back to the focused project when null.

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 precise verb and resource: write the variant fitted/not-fitted matrix to a CSV. It defines the exact table shape (rows, columns, cell values) and distinguishes this tool from proj_list_variants.

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?

It explicitly contrasts this tool with proj_list_variants, clarifying that this export includes every component while the sibling only lists per-variant deviations. That is clear routing guidance, though it does not phrase usage as an explicit when/when-not rule.

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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