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ORF Finder

seq_orf_finder
Read-onlyIdempotent

Find open reading frames (ORFs) on the forward strand (frames 0-2) of a nucleotide sequence. Set a minimum length to filter out short ORFs.

Instructions

Find open reading frames (forward strand, frames 0-2) in a nucleotide sequence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sequenceYesNucleotide sequence (DNA or RNA; case-insensitive). IUPAC ambiguity codes (R, Y, S, W, K, M, B, D, H, V, N) are accepted where documented.
min_lengthNoMinimum ORF length in nucleotides (ORFs shorter than this are filtered out).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
orfsYesOpen reading frames found (empty when none meet min_length).
sequenceYesThe input nucleotide sequence (uppercased; U is normalized to T).
Behavior3/5

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds the behavioral constraint of scanning only the forward strand and frames 0-2, which is useful context. However, it does not disclose other behaviors such as ORF boundary definitions (start/stop codons) or whether stop codons are included, leaving some gaps beyond what annotations cover.

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 a single, concise sentence that front-loads the action ('Find open reading frames') and then adds the relevant constraints. Every phrase adds value, with no redundant or extraneous text. It is well-structured and appropriately sized.

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?

The description, combined with rich annotations and full input schema coverage, provides a solid understanding of the tool's behavior and parameters. The output schema exists, so return values are not required in the description. The only minor gap is the lack of a formal definition of what constitutes an ORF (e.g., start/stop codons), but this is likely implied by the tool's domain and the output schema. Overall, it is reasonably complete for a simple analysis tool.

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?

The input schema fully documents both parameters with descriptions, examples, and constraints, so schema coverage is 100%. The description itself adds no further parameter-specific detail, thus it does not improve upon what the schema already provides. A baseline score of 3 is appropriate.

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 clearly states the tool's function: finding open reading frames. It specifies the forward strand and frames 0-2, which distinguishes it from sibling tools like seq_translate or seq_motif_scan. The verb 'Find' and resource 'open reading frames' are specific and unambiguous.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention any exclusions or refer to sibling tools. An agent must infer usage from the purpose alone, which is not sufficient for comparative decision-making.

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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