Detalhes de doença rara
get_disease_detailFenótipos HPO, genes, SUS, trials, descrição clínica em PT.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| orphaCode | Yes |
raras
TDQS
C2.8/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only lists data fields returned, but does not describe side effects, read-only nature, error behavior, or authorization requirements. This is minimal content disclosure rather than behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence listing five key content types with zero filler. It is front-loaded and every word adds value. The comma-separated structure is easy to parse, making it appropriately sized for the level of detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (returns multiple types of information) and lack of annotations/output schema, the description is incomplete. It does not state the required input, output format, or any constraints. The agent lacks essential context to use the tool effectively, especially without usage or parameter guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter (orphaCode) with 0% description coverage, and the description does not explicitly explain the parameter's meaning. It indirectly implies that the code identifies a disease by mentioning 'doença rara' and listing disease-related data, but the agent is left to infer that orphaCode is the disease identifier. No format or example is given.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description lists the specific content types (HPO phenotypes, genes, SUS, trials, clinical description in PT), which clearly indicates the tool retrieves a comprehensive detail view for a rare disease. The name and title reinforce the purpose, and the list distinguishes it from sibling tools that focus on subsets (e.g., get_sus_coverage, find_papers_for_disease). However, the description lacks an explicit verb like 'retrieves', relying on the tool name for action clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention use cases, prerequisites, or exclusions. Sibling tools exist for specific aspects (e.g., find_similar_diseases, get_sus_coverage), but no comparison or selection criteria are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Try in Browser
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
B3/5.0
Disambiguation4/5
Most tools have clear, distinct purposes, but there is a cluster of 'find' tools (find_similar_diseases, find_phenotypically_similar, find_diseases_by_phenotypes) that could be confused; descriptions differentiate them (semantic vs HPO similarity vs exact match), and the paper search tools also differ by input type. Overall, ambiguous pairs are explicitly disambiguated, leaving only a few close calls.
Naming Consistency5/5
All tools consistently follow a snake_case verb_noun pattern, using a limited set of verbs (analyze, explain, find, get, search) that map predictably to tool functionality. No mixed conventions or vague names are present, making the naming highly systematic.
Tool Count4/5
At 20 tools, the server is slightly above the ideal range of 3-15, but each tool serves a distinct function within the rare disease knowledge platform. The breadth of features—search, similarity, detail, evidence, literature, hypotheses, graph exploration—justifies the count without feeling bloated or redundant.
Completeness5/5
The tool surface comprehensively covers the rare disease domain: search, differential diagnosis, disease detail, evidence, SUS/trials, reference centers, literature, hypotheses, and graph analytics. Write operations are not expected for a read-only knowledge base, and the inclusion of research log and recent updates closes all apparent gaps.