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by com.seqbench

Deep plasmid annotation (pLannotate)

plasmid_deep_annotate
Read-onlyIdempotent

Annotate a plasmid against pLannotate's open-source feature library — a much larger signature set (GenoLIB parts + Swiss-Prot + FPbase + Rfam, cross-referenced against ~195k Addgene-deposited plasmids) than plasmid_annotate's built-in curated list, and it reports partial and low-identity hits as graded alignments rather than the pass/fail signature match plasmid_annotate does (that one is not exact-only either — signatures of 20 bp or more tolerate up to ~10% mismatches — but it reports a hit or nothing, with a mismatches count and an exact flag). Each feature here carries its percent identity, reference coverage and a fragment flag so you can judge a weak hit. Runs a multi-second search on a shared service and is therefore rate limited (see 429/503); use plasmid_annotate for an instant, unmetered first pass.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
circularNoTreat the sequence as a circular plasmid (vs. linear).
sequenceYesNucleotide sequence (raw or FASTA). A, C, G, T, N only — other IUPAC codes are rejected rather than silently dropped, because pLannotate's search engines discard them and every coordinate after would shift. Max 30,000 bp.

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnly and idempotent hints, but the description adds substantial behavioral context: multi-second runtime, shared-service rate limiting (429/503), reporting of partial/low-identity hits with percent identity, reference coverage, and fragment flags. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but well-structured, starting with the primary action, then comparing to the sibling, then detailing output attributes and usage caveats. It is slightly long due to parentheticals, but each sentence earns its place and front-loads key information.

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 complex tool with no output schema, the description explains the nature of returned data (graded alignments, per-feature metrics) and covers performance and rate-limit context. It lacks an explicit description of the full return format, but the provided information is sufficient for selection and invocation.

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 baseline is 3. The description does not add parameter-specific details beyond the schema, but the schema already fully explains the sequence and circular parameters. No extra semantic value provided.

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 annotates a plasmid against pLannotate's feature library, using a specific verb and resource. It distinguishes itself from the sibling plasmid_annotate by emphasizing a larger signature set and graded alignments for partial hits.

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

Usage Guidelines5/5

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

Explicitly names plasmid_annotate as the alternative for an instant, unmetered first pass, and describes when the deep annotation is appropriate (when judging weak hits, needing more comprehensive library). Also mentions rate limits, giving practical usage context.

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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TDQS

A3.6/5.0
Disambiguation4/5

Most tools have highly specific purposes (e.g., crispr_grna_design vs base_editing_design vs prime_editing_design). However, there is some overlap in sequence analysis tools (characterize_sequence, sequence_report) and plasmid annotation tools (plasmid_annotate vs plasmid_deep_annotate) which could cause confusion.

Naming Consistency3/5

The naming pattern is largely consistent with snake_case verb_noun or noun_descriptor (e.g., primer_design, plasmid_annotate, fastq_trim). However, there are exceptions like 'batch', 'workflow', 'gc_content', and 'cloning_diagnose' which don't follow the verb_noun pattern consistently. Also, some names are phrases like 'golden_gate_from_parts'.

Tool Count2/5

With 101 tools, this server is extremely large and likely overwhelming for agents. Even for a comprehensive bioinformatics toolkit, this exceeds a manageable scope, risking agent confusion and inefficient tool selection. A more modular approach would be advisable.

Completeness4/5

The tool surface covers a wide range of bioinformatics workflows including sequence analysis, primer design, cloning, CRISPR, NGS, expression analysis, and data export. There are minor gaps such as lack of a dedicated protein structure prediction tool and limited off-target genome coverage, but overall the set is impressively complete for its domain.

Resources