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berntpopp
by berntpopp

Resolve Cross-Reference

resolve_xref
Read-onlyIdempotent

Resolve external cross-references (OMIM, MONDO, ICD-10, etc.) to matching Orphanet disorders. Returns paginated matches.

Instructions

Resolve an external cross-reference CURIE (OMIM/MONDO/ICD-10/ICD-11/UMLS/GARD/MeSH/MedDRA) back to the Orphanet disorder(s) that map to it. Returns matches[] plus a pagination block {total, returned, limit, offset, truncated, next_offset}; when truncated, next_commands carries a forward-page step. Miss semantics (list-shaped, unlike resolve_disease): a malformed CURIE is rejected with invalid_input, while a well-formed but unmapped CURIE returns an empty page (total: 0), not not_found. Signature: resolve_xref(xref_id, limit=, offset=, response_mode=).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax matches (default 50).
offsetNoRows to skip for forward paging (default 0).
xref_idYesAn external cross-reference CURIE (prefix:local), e.g. OMIM/MONDO/ICD-10, to resolve back to the Orphanet term(s) that map to it.
response_modeNoVerbosity: minimal|compact|standard|full (default compact).compact
Behavior5/5

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

Beyond the annotations (readOnly, idempotent, openWorld), the description details pagination behavior (truncated, next_commands), distinguishes between malformed (invalid_input) and unmapped (empty page) CURIEs, and discloses the return structure. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (3-4 sentences) and front-loaded with the main purpose. It efficiently conveys key behavioral nuances. Slightly more structured formatting could improve readability, but it is well within acceptable limits.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, the description thoroughly explains return fields (matches, pagination block, next_commands) and error cases. No critical information about behavior or usage is missing for a tool with 4 parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description lists the signature but adds little beyond the schema’s existing descriptions and examples. The extra detail about miss semantics does not directly enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool resolves external cross-reference CURIEs (OMIM/MONDO/ICD-10/ICD-11/UMLS/GARD/MeSH/MedDRA) to Orphanet disorders. It explicitly distinguishes from the sibling 'resolve_disease' by noting different semantics (list vs. single result), making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for use: resolving external identifiers. It contrasts with resolve_disease regarding pagination and miss semantics, and explains error handling (invalid_input vs. empty page). While not explicitly stating when not to use, the differentiation effectively guides selection.

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

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