plasmid_annotateAuto-detect common cloning features (promoters, tags, origins, resistance markers, MCS, primers) on both strands. Signatures under 20 bp must match exactly; longer ones tolerate up to ~10% mismatches so point mutants still annotate — each feature reports its own mismatches count and an exact flag.
| Name | Required | Description | Default |
|---|---|---|---|
| sequence | Yes | Nucleotide sequence (raw or FASTA; IUPAC accepted). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond annotations by disclosing specific matching behavior: exact match required for signatures under 20 bp, ~10% mismatch tolerance for longer signatures, and each feature reporting a 'mismatches' count and 'exact' flag. It also mentions both strands are examined. These are valuable behavioral details not present in the readOnlyHint or idempotentHint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) and front-loaded with the core purpose. It lists featured feature types and key behavioral constraints without fluff. No redundant words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter, read-only tool with no output schema, the description covers the main behavior and even hints at the output (mismatches/exact flags). However, it does not describe the overall return structure (e.g., a list of features with locations). Still, it is sufficiently complete for straightforward annotation use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'sequence' already has a complete description in the schema ('Nucleotide sequence (raw or FASTA; IUPAC accepted).'). The tool description adds no additional parameter-level detail beyond this. Since schema coverage is 100%, baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: auto-detecting common cloning features (promoters, tags, origins, resistance markers, MCS, primers) on both strands. This is a specific verb+resource combination and the list of feature types distinguishes it from generic sequence analysis tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Sibling tools like plasmid_deep_annotate and plasmid_full_report exist, but the description does not mention them or any context where this tool is preferred. It only states what it does, not when to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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'.
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.
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.