workflowRun a multi-tool pipeline over many records. steps is an ordered list of { tool, args?, from? }; each step's chained sequence feeds the next by default. input is multi-FASTA or one sequence per line.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | Multi-FASTA or one sequence per line. | |
| steps | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and idempotentHint=true, but the description says 'Run a multi-tool pipeline' which hints at execution, creating ambiguity about side effects. The description adds no additional behavioral context (e.g., what gets destroyed, auth needs, rate limits). It does not clarify the read-only nature, and the term 'Run' may mislead.
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?
Two sentences with no wasted words. The first sentence front-loads the purpose, the second provides key parameter details. Efficient and clear.
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?
Given the tool's complexity (multi-step pipeline), the description covers core behavior and basic parameter structure but omits error handling, failure behavior, output format, and edge cases. No output schema exists, so this gap is notable. Adequate but incomplete for a complex tool.
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 description adds meaning beyond the schema: it explains that `steps` is an ordered list with structure { tool, args?, from? } and that chained sequences feed the next by default. This clarifies chaining behavior not present in the schema. Schema coverage is low (only `from` described), so description compensates partially.
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 it 'Run[s] a multi-tool pipeline over many records', identifying the verb and resource. The title reinforces 'Batch workflow (multi-tool pipeline)'. However, it does not explicitly differentiate from sibling tools like individual analysis tools, though unique in being a pipeline runner.
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?
The description explains that steps is an ordered list and that each step feeds the next, implying chaining behavior. It also specifies input format. No explicit when-to-use or when-not-to-use guidance or alternatives are mentioned, relying on the user to infer from sibling context.
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.