Noodle Biomedical Literature Discovery MCP

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the essential behavioral traits. The description adds only the purpose caveat, not new behavioral context like return format or rate limits. Since annotations are strong, a neutral score is appropriate.

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?

Two short sentences with no filler. The main action and metadata list are front-loaded, and the use-case caveat is a single clause. Every word earns its place.

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?

With no parameters and an output schema present, the description sufficiently conveys what the tool does, what it returns, and its intended use. Nothing needed for correct invocation or interpretation is missing.

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 zero parameters, so the description has nothing to add. Per the rubric, 0 params earns a baseline of 4. The description correctly omits any parameter details since none exist.

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?

Clear verb 'Return' plus specific resource 'corpus summary' and the exact metadata types (coverage, source, freshness, count). It clearly distinguishes itself from siblings which are about individual publications/works, and includes the intended use case in the second sentence.

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 the general purpose ('literature discovery and professional review') and a restriction ('not diagnosis or treatment'), but does not explicitly contrast with sibling tools or state when to choose this over get_publication_details or search_biomedical_literature. The usage context is implied by the resource, but not explicit exclusions are given.

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 cover read-only, idempotent, non-destructive behavior. The description adds useful context about returning a complete public bibliographic record and the intended literature-discovery purpose, but it does not disclose additional behavioral details beyond those 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?

Two concise sentences front-load the core action and scope, with the usage caveat kept brief. Every sentence contributes meaningful 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?

For a single-parameter, read-only lookup with a full input schema and an output schema present, the description covers what the tool does, when to use it, and its appropriate context. No critical information is missing for correct invocation.

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 input schema fully documents the only parameter, pmid, including format and meaning. The description adds no significant parameter-level detail, so baseline 3 is appropriate.

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 ('Retrieve'), a specific resource ('one complete public bibliographic record'), and the exact identifier type ('by PMID'). This clearly separates it from sibling search or neighborhood tools, which have different scopes.

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 phrase 'after search' gives clear context that this tool is used to retrieve details for a PMID already identified via search. It does not explicitly name alternatives or state when not to use it, but the intended usage is reasonably clear.

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, idempotentHint, and destructiveHint, covering the safety profile. The description adds useful context like 'bounded neighborhood' and a disclaimer about non-clinical use, which go beyond metadata. However, it does not explain specific behaviors such as pagination or limits, so it provides only moderate added value.

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 concise sentences with no filler. The core action is front-loaded, and the disclaimer is brief. Every word contributes to clarity, making it an exemplar of efficient writing.

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 tool with an output schema and annotations covering safety, the description provides sufficient context. It states the purpose and the non-clinical usage, which is important. The only gap is the lack of explicit differentiation from get_work_neighborhood, but that falls under usage guidance rather than completeness. Overall, it is well-rounded for the tool's complexity.

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%, with both pmid and from_work_id fully documented in the schema. The description adds no additional parameter-specific details, so it does not exceed the baseline score for a high-coverage schema. The agent can rely on the schema for parameter meaning.

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 uses a specific verb ('Retrieve') and resource ('bounded citation and semantic neighborhood') scoped to one PMID. It clearly identifies the tool's function, but does not explicitly distinguish it from sibling get_work_neighborhood, which is a closely related alternative. The name and title help, but explicit differentiation is absent.

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of conditions like 'use for PMID-based exploration' or reference to sibling tools. The description simply states what it does, leaving the agent to infer appropriate usage from context.

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, covering safety. The description adds value by specifying the record is 'complete' and 'public', and by adding the non-diagnostic disclaimer—context beyond the structured 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?

Two sentences with no redundancy; the primary action and scope are front-loaded, followed by a brief application note. Every sentence earns its place.

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?

With an output schema present and annotations covering safety, the description is complete for the tool's simple purpose. The only gap is lack of sibling differentiation, but given low complexity and available structured data, the provided text 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 coverage is 100% (the lone work_id parameter has a clear description: 'Canonical Noodle Literature Corpus work identifier'). The tool description adds no new semantics for the parameter, just restates the identifier concept—appropriate given high coverage, but not additive.

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 a specific verb ('Retrieve') and resource ('one complete public bibliographic record') keyed by a Noodle work identifier. It does not explicitly differentiate from sibling tools like get_publication_details, but the single-record-by-ID focus is unambiguous.

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 includes a usage disclaimer ('for literature discovery and professional review, not diagnosis or treatment') which implies appropriate contexts, but there is no explicit guidance on when to choose this tool over siblings or when not to use it. The use case is only implied.

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 cover read-only, idempotent, non-destructive behavior, lowering the burden. The description adds meaningful context by describing the result as 'bounded' and clarifying that it is for discovery/review rather than clinical use. It does not describe pagination or limits, but the output schema covers return structure and the annotations cover safety traits.

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 filler. It front-loads the core action, states the scope, and adds a relevant boundary about appropriate use. Every sentence earns its place.

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, idempotent retrieval tool with one required parameter and an existing output schema, the description is largely complete. It covers the purpose, scope, and appropriate-use boundary. The main gap is the absence of an explicit routing cue to sibling tools, but that gap is modest given the schema and annotations.

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 input schema provides 100% parameter coverage, including descriptions for work_id and from_work_id, so the description adds little new parameter-level meaning. It only reinforces that the tool centers on 'one Noodle work identifier,' which is already in the schema. Baseline 3 is appropriate.

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 clear action ('Retrieve the bounded citation and semantic neighborhood') and a specific resource ('one Noodle work identifier'). It distinguishes the tool from detail/search siblings by focusing on neighborhood retrieval, though it does not explicitly name the distinction from get_publication_neighborhood.

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 useful context ('for literature discovery and professional review') and an exclusion ('not diagnosis or treatment'), so an agent can infer appropriate situations. However, it does not explicitly say when to use this tool versus get_publication_neighborhood, get_work_details, or search_biomedical_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?

The description adds behavioral context beyond the annotations: the corpus is public and PubMed-derived, the search is semantic rather than keyword-only, identifiers anchor results, and results are not suitable for medical decisions. The readOnlyHint, idempotentHint, and destructiveHint are not contradicted.

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 front-loaded, purposeful sentences with no filler: the first states what the tool does, the second gives query-construction guidance, and the third sets scope/limitations. Every sentence earns its place.

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 annotations, full schema coverage, and presence of an output schema, the description covers all essential operational context: corpus scope, semantic-search behavior, identifier-anchoring strategy, and intended use limitations. Nothing an agent needs to call this tool correctly is missing.

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 description adds value beyond the schema by telling agents to include known identifiers in the query as 'exact anchors,' which clarifies effective use of the query parameter. Other parameters (sort, limit, cursor) are already well documented in 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 uses a specific verb and resource: 'Semantically search Noodle's public PubMed-derived biomedical corpus.' This clearly differentiates the tool from siblings like get_publication_details or get_corpus_summary, which retrieve specific entities or summaries rather than perform corpus-wide semantic 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 gives explicit query guidance: include known PMID, DOI, or PMCID identifiers so they can act as exact anchors. It also states the appropriate context ('literature discovery and professional review') and excludes diagnosis or treatment, providing clear usage boundaries without naming sibling alternatives.

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, idempotentHint, and destructiveHint false; the description adds genuinely valuable reassurance that invoking the tool 'initiates no payment or outreach and changes no scientific result.' That guards against an agent wrongly assuming the 'Support' title triggers a donation. No contradiction 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.

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

Two tight sentences, both earning their place: the first front-loads the core purpose, the second removes any misconception about payment/outreach. Only minor loss — it is terse on what the Helena Good MCP is — keeps it from a 5.

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 tool that has its own output schema, the description gives the agent everything needed to safely invoke it: read-only, idempotent, and side-effect free. There is no critical missing detail for correct invocation.

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?

Tool has zero parameters, so the 100% coverage baseline (score 4) applies; there is nothing for the description to explain about params. It correctly focuses on the action's semantics and lack of side effects instead.

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?

Delivers a specific verb ('Learn about') and resource ('the separate Helena Good MCP'), and clarifies the action is purely informational — which sets it apart from the sibling data-retrieval tools. Some vagueness remains about what the Helena Good MCP actually is and what 'support' entails, keeping it from a 5.

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 only implicitly differentiates this from the sibling data-access tools (get_corpus_summary, search_biomedical_literature, etc.) by labeling itself an information action. It never states explicitly when to reach for it, when not to, or names any alternative as a fallback.

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