AGR MCP Server

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the tool executes pre-built queries, requires parameter formatting (numeric keys, simple/full formats), and references a sibling tool (mine_list_templates) for discovery. However, it lacks details on error handling, performance, or output structure.

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 well-structured and front-loaded: the first sentence states the core purpose, followed by parameter format details, examples, and a clear call-to-action for template discovery. Every sentence adds value without redundancy, making it efficient for an agent to parse.

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 (3 parameters, nested objects, no output schema, no annotations), the description is largely complete: it covers purpose, usage, parameter semantics, and references sibling tools. However, it lacks details on output format or error cases, which could be helpful for an agent invoking the 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?

Schema description coverage is 100%, so the baseline is 3. The description adds significant value beyond the schema: it explains parameter format (numeric keys, simple vs. full), provides concrete examples (e.g., BRCA1, HGNC:1100), and lists common template names with usage context, enhancing understanding of how to structure params effectively.

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 purpose: 'Run a pre-built query template with parameters.' It specifies the action ('Run'), resource ('pre-built query template'), and distinguishes it from sibling tools like mine_list_templates (for discovery) and other gene-specific tools by focusing on template execution with parameterized queries.

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 provides explicit guidance on when to use this tool: for running templates discovered via mine_list_templates. It distinguishes it from alternatives by listing common templates (e.g., Gene_Orthologs vs. get_gene_info) and implies not to use it for direct queries (use mine_query or mine_natural_query instead).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.