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Glama

translate_sequence

Translate DNA or RNA sequences into protein in one reading frame or all six. Supports FASTA input and stop codon handling for gene analysis.

Instructions

Translate DNA/RNA to protein, in one frame or all six.

Uses the standard genetic code; stop codons appear as '*'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
frameNoReading frame; negative = reverse complement; 'all' = six frames.
to_stopNoStop at the first stop codon.
sequenceYesA raw sequence or FASTA text (one or more records).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden and does add real context: the standard genetic code is used and stop codons render as '*'. However, it omits what happens with ambiguous bases, non-multiple-of-3 input, or invalid characters, which matters for a sequence-translation tool.

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?

Two short sentences, front-loaded with the core operation followed by the key output convention. Every sentence carries information and there is no 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?

An output schema exists, so return formatting need not be explained, and the description covers the translation semantics and stop-codon convention. The only gap is behavior on multi-record FASTA input and malformed sequences, which is minor given the complete schema.

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%, so the schema already documents frame (including negative/reverse-complement and 'all'), to_stop, and the FASTA-capable sequence input. The description only loosely echoes the frame behavior ('one frame or all six'), adding little beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Translate DNA/RNA to protein') plus the scope of frames, so an agent knows exactly what the tool produces. It does not distinguish itself from the sibling find_orfs, which also translates nucleotide sequence, so the sibling-differentiation credit is missing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'in one frame or all six' implies when a given frame mode is appropriate, but there is no explicit guidance on when to use this tool rather than find_orfs (which surfaces ORFs) or seq_stats. Usage is inferable rather than stated.

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