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ianderso
by ianderso

parse_dna_segments

Read-only

Parse shared-segment data to check a match file before recording. Returns segments, totals, and flags unreadable input instead of zero shared DNA.

Instructions

Parse pasted shared-segment data into structured segments and totals.

Use this to check what a match file actually contains before recording it. Returns each segment plus the total and largest-segment centiMorgans.

If nothing parses, parsed is false and the reason is given. That distinction matters: the server answers unreadable input with zero segments and a success status, which would otherwise read as "this person shares no DNA" rather than "I could not read that".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesRaw shared-segment data, as a testing company exports it: rows of chromosome, start, stop, centiMorgans, SNPs, separated by commas or tabs, with an optional side of M, P or U. A header row is tolerated.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and openWorldHint=false, and the description adds substantial context beyond them: the return shape (segments, total and largest-segment centiMorgans) and the crucial failure semantics where `parsed` is false with a reason, explicitly contrasted against the server's misleading zero-segment success response.

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?

Front-loads the purpose in one sentence, then usage, then return values, then the subtle failure case. Every sentence carries distinct information and none is redundant with the schema or annotations.

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?

With no output schema, the description still tells the agent what comes back (segments, total cM, largest-segment cM, `parsed` flag plus reason) and warns about the zero-segment/success ambiguity. Nothing needed to interpret a result correctly is missing.

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% and the schema field already specifies the CSV/TSV row format, optional side letter and tolerated header row. The description adds only the framing term 'pasted shared-segment data', so the schema does the heavy lifting and the baseline 3 applies.

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?

States a specific verb and resource ('parse ... shared-segment data into structured segments and totals') and clearly separates itself from the DNA-writing siblings like add_dna_match and the reading sibling get_dna_matches. An agent can identify the tool's job without opening the schema.

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?

Gives concrete usage context ('check what a match file actually contains before recording it'), which implies the workflow position relative to add_dna_match. It does not, however, explicitly name that sibling or state when not to use this tool, so it falls short of a full when/when-not/alternatives map.

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