biorxiv-mcp-server

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

Beyond the readOnlyHint and openWorldHint annotations, the description discloses best-effort Markdown quality, approximate section structure, per-version caching for an hour, parallel server resolution, error behavior, and fallback conditions. This is rich behavioral context that an agent cannot infer from the annotations or schema.

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 long but every sentence carries distinct information: extraction method, server resolution, quality caveat, paging/caching, error fallback, and journal alternative. It is front-loaded with the core retrieval purpose and progresses logically through operational details.

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 tool with this complexity, the description covers the key operational facts: DOI resolution, paging through long articles, likely error modes and their fallback, and the approximate nature of the extracted structure. Since an output schema exists, detailed return-value documentation is not needed.

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?

With 100% schema description coverage, the baseline is 3, and the description adds value by explaining the paging protocol (offset = prior_offset + prior_length), the caching implications for later chunks, and how server resolution works. It complements the schema rather than merely restating 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 first sentence states a specific verb+resource: 'Retrieve a preprint's full text as best-effort Markdown, extracted from its rendered HTML article page,' and then names the concrete content extracted (abstract, sections, references). It differentiates itself from siblings by explicitly contrasting with biorxiv_get_preprint and the journal-published version, and by stating this is not structured JATS.

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 routing guidance: when a fulltext_unavailable error occurs, use biorxiv_get_preprint for metadata; when a preprint has a journal version, richer full text may live elsewhere. It also specifies when to use offset and limit for paging rather than one call, making the selection and invocation conditions 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?

With readOnlyHint, openWorldHint, and idempotentHint already set, the description goes well beyond them by disclosing batch behavior, per-DOI failure reporting with reasons, retryable flags, rate-limit wait times, and the fact that all revisions are returned in one response. This is rich, non-obvious behavioral context that annotations alone do not 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 front-loaded with the core purpose and every subsequent sentence adds necessary behavioral or constraint information. It is dense but not bloated; each 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 batch lookup tool with an output schema, the description covers the essential operational details: what is fetched, how revisions are returned, server selection, failure semantics, retryability, and DOI format requirements. Nothing critical is missing for an agent to select and invoke this tool correctly.

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 by specifying the DOI pattern (10.NNNN/…), the default behavior of server='both', and how failures are handled per DOI. These details go beyond the schema's parameter descriptions without duplicating them.

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 action ('Fetch full metadata, abstract, all revision history, JATS XML full-text links, and published-journal DOI') and a specific resource (preprints by DOI). It is clear and detailed, but it does not explicitly differentiate itself from siblings like biorxiv_get_fulltext or biorxiv_get_published_version, which could have overlapping responsibilities.

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 clear context for when to use the tool: given one or more preprint DOIs, it returns metadata and revisions. It also explains the server='both' default behavior. However, it does not explicitly state when NOT to use it or which sibling to choose instead, so it lacks explicit exclusion guidance.

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 mark the tool as read-only, idempotent, and open-world, but the description adds meaningful behavior beyond that: the shared 10.1101/ prefix rationale, parallel checking when server='both', the server-reported-in-response behavior, and the not-found error condition. No contradiction with annotations exists.

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 dense but well-structured: purpose first, then when-to-use, then parameter behavior, then error handling. Every sentence contributes necessary operational information, and nothing is redundant with the schema.

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?

The description is complete for a two-parameter tool with a rich output schema. It covers the target input, default behavior, error case, and relationship to the sibling tool. Given the annotations and output schema, nothing an agent needs to call this 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?

The input schema already documents both parameters fully, so the baseline is 3. The description adds extra meaning for the `server` parameter by explaining why 'both' is the default, how parallel checking works, and how the shared DOI prefix makes server selection ambiguous. This raises it above baseline.

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 action and resource: 'Resolve a preprint DOI to its full journal publication record' and lists the returned fields. It clearly differentiates itself from biorxiv_get_preprint by focusing on the published journal crosswalk rather than the preprint record.

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?

It gives an explicit trigger condition: use when `publishedJournalDoi` from biorxiv_get_preprint is present and full crosswalk metadata is needed. It also tells the agent when not to use it and what to call instead: check biorxiv_get_preprint if confirmation of publication is the goal. Server selection guidance is also included.

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 readOnlyHint, idempotentHint, and openWorldHint, so the base safety profile is established. The description adds useful behavioral context beyond those annotations: the returned values are 'current valid values' and should be fetched before filtering, indicating the category list may change over time. This is valuable guidance without contradicting any annotation.

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, each earning its place: the tool's purpose, how to use the output, and when to run it. The most important information is front-loaded, with no redundant or decorative language. This is an example of efficient, well-structured documentation.

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 zero-parameter read-only tool with an output schema present, the description covers everything an agent needs: what values are returned, how to consume them, and when to call it. The existence of an output schema means return-value details are already structured, so no further explanation is required.

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 takes zero parameters, so there is nothing for the description to clarify about parameters. Per the baseline for zero-parameter tools, this dimension is trivially satisfied and needs no compensation. The description appropriately focuses on the output semantics 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?

The description opens with a specific verb and resource: 'List valid subject category strings for bioRxiv and medRxiv.' It clearly distinguishes this tool from its siblings by identifying categories as its domain, not fulltext, preprints, or search. The purpose is unambiguous and tied to a concrete use case.

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 tells the agent when to use this tool: before filtering with biorxiv_list_recent, and how to apply the result (as the `category` filter value). It names the sibling tool directly and gives an actionable sequence, leaving no ambiguity about its role in the workflow.

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?

Goes far beyond the readOnlyHint/openWorldHint annotations: discloses fixed 30-per-page pagination, integer-offset cursor semantics, per-server cursor state under server="both", partial-failure semantics (one server failing yields a partial result with failed[]), and full-failure semantics (abort with retryable upstream_unavailable/rate_limited). Even explains the rationale (empty-page ambiguity), which materially helps an agent interpret results and decide retries. Consistent with annotations — no contradiction.

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 earning its place: purpose first, then pagination mechanics, then dual-server pagination, then partial and full failure modes, then category routing. It is front-loaded and logically ordered. The length is fully justified by the genuinely complex behavioral semantics (partial results, per-server cursors, retryable errors) that an agent must understand to use the tool correctly.

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 an output schema exists (return shape need not be described) and annotations cover the safety profile, the description covers every operationally critical aspect: page size, cursor stepping, dual-server pagination, partial vs. aborted failure, retryable error types, and where to obtain valid category strings. Nothing an agent needs to invoke or interpret 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 baseline is 3; the description adds genuine value on top. For `cursor` it explains the fixed page size and offset stepping (0, 30, 60…); for `server` it details the 'both' fan-out consequences, per-server pagination, and failure behavior; for `category` it routes to the authoritative source. Only start_date/end_date add nothing beyond the schema, which is fine since the schema already specifies YYYY-MM-DD.

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 a specific verb+resource+scope: 'List preprints posted or revised within a date interval, optionally scoped to one server or a subject category.' This clearly distinguishes it from sibling tools: search_preprints (query-based), get_preprint/get_fulltext/get_published_version (single-item retrieval), and list_categories (categories, not preprints).

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 intended use context is clear — browsing preprints by date interval with optional server/category scoping — and it explicitly routes to biorxiv_list_categories for valid category values. However, it never contrasts itself with biorxiv_search_preprints or states when NOT to use this tool, leaving the list-vs-search decision to inference.

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 signal read-only and open-world behavior, but the description adds substantial value: EuropePMC indexing delay of 1–2 days, rate-limit failure semantics with retryable errors, and enrichment failure handling via enrichment_error: "rate_limited". No contradiction with annotations exists.

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?

Every sentence earns its place: core behavior, parameter combination rule, recency caveat with alternative, and error behavior. The most important functional information is front-loaded, and the content is dense without fluff.

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?

The description is complete for a search tool with a rich output schema and annotations. It covers behavior, default scope, timing caveats, error handling, and the key alternative, leaving nothing necessary for an agent to call it correctly.

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 does not meaningfully add beyond the schema: the AUTH mapping and ANDing of author is already in the author parameter description, and the server default is already in the server parameter description. The description reinforces usage constraints but does not introduce new parameter semantics.

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: search preprints by keyword and/or author, with EuropePMC relevance ranking and bioRxiv/medRxiv metadata enrichment. It is clearly differentiated from siblings like biorxiv_get_preprint and biorxiv_get_fulltext by framing this as a search/enumerate operation, and it even names biorxiv_list_recent as the alternative for very recent preprints.

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 usage context: supply a keyword, an author, or both; author is ANDed with the keyword. It also gives a concrete when-not-to-use rule by directing users to biorxiv_list_recent for preprints posted within the last day, and it notes the default server coverage.

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