Folklore Clinical Variant Interpretation MCP

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

The annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description's read-only framing is consistent rather than novel. It adds meaningful context by describing the complete return payload, the corpus scope, retraction status, and the statement that it contains no patient context.

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 compact and front-loaded, starting with the core action and resource, then summarizing key return fields, then giving usage guidance, and ending with a relevant caveat. Every sentence contributes useful information without redundancy.

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 small single-parameter input schema, rich annotations, and the presence of an output schema, the description supplies the essential context an agent needs: what the tool returns, when to call it, and what it does not contain. No significant gap remains.

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 schema already fully documents the single 'pmid' parameter with a detailed description and validation pattern, so schema coverage is high. The description adds only the singular lookup context and not new parameter-level details, which meets the baseline but doesn't exceed it.

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 states a specific action and resource: 'Retrieve the complete public bibliographic record for one PMID from Folklore's PubMed-derived genetics corpus.' It also distinguishes itself from the sibling search tools by emphasizing a single-record lookup with a comprehensive result set.

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 explicitly says 'Use after literature search when a user asks to inspect a specific publication,' giving clear contextual guidance. It doesn't explicitly name alternatives or exclusions, but the intended role relative to the sibling tools is evident.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false; the description adds meaningful context by stating it returns 'source-linked evidence candidates for professional review, not diagnoses, causality claims or treatment recommendations.' This safety caveat goes beyond the structured annotations.

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?

Three sentences front-load the core purpose, provide a concrete usage rule, and close with an important caveat. There is no filler or repetition of schema contents.

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?

For a read-only search tool with a rich output schema and fully documented parameters, the description covers the essential invocation behavior, accepted input classes, and professional-review caveat. It is slightly incomplete only in not routing the agent between overlapping sibling search tools.

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 input schema already documents query, sort, limit, and cursor well. The description reinforces the query semantics (e.g., PMID/DOI/PMCID as anchors) but adds little parameter-level detail beyond the 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?

The description names a specific verb and resource: semantically search the public scientific Literature Corpus by natural-language question, and lists accepted identifier/concept types. It is clear on its own, but the title's 'Folklore Literature Corpus' conflicts slightly with the description's 'scientific Literature Corpus,' and it does not explicitly distinguish itself from sibling search_variant_literature.

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 gives concrete usage guidance: include every known publication identifier when the user wants to compare papers or find work related to a specific paper. It establishes clear context but does not state when not to use this tool versus sibling search tools such as search_variant_literature.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the bar is lowered; the description still adds meaningful context beyond them: output is decision-support with explicit limitations, the tool does not evaluate patient context, results must not be framed as diagnosis/treatment, and it refuses to select a candidate when resolution is ambiguous. These are behavioral traits that materially shape how an agent should invoke and present the results.

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?

Six sentences, each carrying distinct information: usage triggers, scope, input forms, return contents, safety limitations, and ambiguity policy. It is front-loaded with the highest-value routing information and, while slightly verbose, the density is justified for a medical-reasoning tool with safety implications.

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?

For a complex ACMG/AMP classification tool, the description covers what to pass, what comes back, scope limits, and safety constraints, with an output schema available to document return structure. An agent has everything needed to decide when to call it and how to responsibly handle the result.

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 coverage is 100%, so the baseline is 3; the query and assembly parameters are already well documented in the schema. The description adds useful scope constraints not fully explicit in the schema (germline SNV or simple indel <50 bp, GRCh38-only), but it mostly restates accepted input forms already enumerated in the query parameter description.

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 opens with explicit user-intent triggers ('classify or interpret pathogenicity, review a VUS, check available ClinVar assertions or population-frequency evidence, or resolve a variant notation') and states a precise scope: one public GRCh38 germline SNV or simple indel smaller than 50 bp. This clearly differentiates it from the literature-oriented siblings (search_variant_literature, get_publication_details), which concern publications rather than variant interpretation.

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?

Provides explicit 'Use when...' triggers covering classification, VUS review, evidence checking, and notation resolution, plus a clear exclusion: it does not evaluate patient context and must not be presented as a diagnosis or treatment recommendation. It does not explicitly name sibling literature tools as alternatives, but 'Never choose a candidate when resolution is ambiguous' adds practical guidance on when to abstain from answering.

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

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

The annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds valuable behavioral context beyond the structure: exact variant mentions rank ahead of broader gene associations, and the results should not be interpreted as establishing causality, pathogenicity, or diagnosis. This compounds the tool's behavior beyond what annotations provide.

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 compact and well-structured: the first sentence explains the core function, the second provides usage guidance, and the third adds an important caveat. Every sentence contributes meaningful information and the critical constraints are front-loaded.

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 output schema, the description does not need to explain return values. It provides the key operational details needed to call the tool correctly: the genome assembly requirement, the ranking behavior, and the clinical classification caveat. It could be slightly more explicit about how gene-level queries are handled, but it is otherwise quite complete for a surgical 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 schema already documents the query, limit, assembly, and question parameters thoroughly. The description reinforces that query is a variant identifier rather than a natural-language question, but this is also present in the schema's parameter description. The description does not add significant new parameter-level meaning beyond the 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?

The description states a specific verb and resource: resolve a GRCh38 variant and retrieve publications from Folklore's PubMed-derived corpus. It differentiates itself from sibling tools by focusing on exact variant mentions ranking ahead of gene associations, which clarifies what makes this tool distinct from a general literature search.

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 explicitly says to use the tool when a user asks what has been published about a variant, gene, or associated condition. It does not mention exclusions or directly name these siblings, but the context is clear enough for an agent to know this tool is appropriate for variant-centric literature questions.

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

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

Annotations already provide readOnlyHint=true, openWorldHint=false, idempotentHint=true, destructiveHint=false. The description adds specific behavioral context beyond these annotations: it explicitly clarifies this is an information action and names precise exclusions (no payment, no relay creation, no result modification). This enriches the agent's understanding of side effects and side-effect-free guarantees, without contradicting the annotations.

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 two sentences with no wasted words. The first sentence front-loads the purpose and mechanism; the second sentence immediately addresses exclusions and behavioral boundaries. Each sentence earns its place, and the structure is efficient for agent consumption.

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?

For a parameterless, read-only, informational tool with output schema present, the description covers all necessary aspects: what it does, how it works (via separate MCP), and what it does not do. Annotations handle safety/behavior, and the absence of parameters removes any parameter-related gaps. Nothing material is missing for an agent to correctly invoke this 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 tool has 0 parameters, so the baseline for parameter semantics is 4. The description adds no parameter-specific information because none is needed; the schema is empty and coverage is 100%. The description's focus on purpose and behavioral constraints is appropriate for a parameterless tool.

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 verb 'Learn how an agent can support or spread' and the resource 'Helena's free public scientific infrastructure'. It explicitly identifies the mechanism ('through the separate Helena Good MCP') and distinguishes itself from the sibling search tools by focusing on support rather than search. The sentence 'This is an explicit opt-in information action' further clarifies the tool's nature, removing ambiguity about whether it performs actions.

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 clear exclusions: 'It does not initiate payment, create a relay, or change any Folklore scientific result,' which tells the agent when NOT to use this tool. It also states it is an 'opt-in information action,' implying it should be used when seeking informational support on spreading Helena's infrastructure. However, it does not explicitly contrast with sibling tools or state when to choose it over alternatives, though the context of sibling search tools makes this reasonably clear.

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