Variants in a gene (by gene symbol), ranked by impact then ESM2 damage. Paginated (limit, default 25); returns total_variants. Use af_min to filter by global AF.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| af_min | No | ||
| gene_symbol | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description covers pagination (limit, default 25), sorting criteria, and the af_min filter. It does not mention read-only status or prerequisites, but these are implied. The output schema existence reduces the need to detail return fields.
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 a single, compact sentence with no wasted words. It efficiently conveys purpose, ranking, pagination, and filtering options.
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 simplicity and the presence of an output schema, the description covers the core aspects: input, sorting, pagination, and a filter parameter. It could mention that gene_symbol must be a valid HGNC symbol, but overall it is sufficient.
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?
Schema description coverage is 0%, but the description explains all three parameters: gene_symbol (target gene), limit (paginated, default 25), and af_min (global AF filter). This adds meaning beyond the bare schema.
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?
Description clearly states the tool retrieves variants for a given gene symbol, ranked by impact then ESM2 damage. This distinguishes it from sibling tools like variant_lookup or variant_search which target specific variants or broader searches.
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 specifies using af_min for filtering, but does not provide guidance on when to use this tool versus alternatives like variant_lookup or variant_search. It lacks explicit context for appropriate use cases.
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.
Tools are mostly distinct with clear purposes, but some overlap exists between disease-related tools (disease_lookup vs disease_links) and between ask and ask_the_graph. Descriptions help differentiate, but an agent might still misselect.
Naming patterns are inconsistent: some tools use verb_noun (ask, search_diseases), others use noun_noun (breed_similarity, disease_bridge), and some use descriptive phrases. No consistent convention observed.
18 tools is well-scoped for a canine genetics knowledge base. Each tool serves a distinct function covering breed, disease, variant, and query capabilities without being overwhelming.
The tool set covers all major aspects of the domain: breed profiles, disease lookup with links, variant querying, semantic search, and metadata. No obvious gaps for the stated educational purpose.
