Citation-health over a CC0 citation graph: what supports, refutes, or cites a paper. Read-only.
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Average 3.8/5 across 5 of 5 tools scored.
Each tool targets a distinct query direction or edge type, but edges_about is a broad catch-all that overlaps with the specialized queries. The descriptions are clear enough that an agent can usually pick the right one.
The names mix 'what_' question forms with noun-preposition forms like edges_about and references_of. They are all lowercase snake_case and readable, but the pattern is not fully consistent.
Five tools is a well-scoped size for a citation graph query server. Each tool covers a meaningful query type without unnecessary redundancy.
The tool surface covers all major edge exploration needs: outgoing references, incoming citations, support/refute relationships, and a catch-all for all edges. There are no obvious dead ends for read-only citation graph queries.
edges_aboutEdges aboutAEvery edge touching the given work or claim, in either direction, each tagged with its trust tier (asserted|inferred) and attribution/provenance.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum edges to return per tier (default 100, max 1000). Well-cited works have thousands; the response reports has_more and inferred_total so you can tell a page from the whole answer. | |
| offset | No | How many edges to skip, for paging. Advance by the LIMIT you asked for, not by the number of results you got back — duplicates are removed after the window is taken, so a page can return fewer rows than it consumed. Keep going while has_more is true. | |
| identifier | Yes | DOI, arXiv id, OpenAlex id, or internal claim id | |
| asserted_only | No | If true, restrict to human-signed (asserted) edges. If false (default), return both asserted and machine-inferred edges. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds behavioral context about returning both directions and tagging edges with trust tier and provenance, but it does not mention pagination, deduplication, or has_more semantics, which are left to the 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?
A single, front-loaded sentence that captures the essence of the tool with zero filler. It names the resource, scope, and key output attributes efficiently, making it easy for an agent to parse quickly.
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 a well-documented schema, the description covers the core purpose and key output details (trust tier, provenance). It omits output shape details like has_more and inferred_total, but those are embedded in the parameter descriptions, and the annotation suite already covers safety, so the overall context is adequate though not exhaustive.
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 fully documents all four parameters. The description does not add parameter-specific meaning beyond what the schema already provides, so the baseline of 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 resource (edges touching a work/claim), scope (every edge, in either direction), and output tagging (trust tier and attribution/provenance). This clearly distinguishes it from the directional sibling tools like what_cites or references_of without needing to open their schemas.
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 explicit when-to-use or when-not-to-use guidance is given. The description's 'every edge ... in either direction' implies it is the comprehensive edge query, and the sibling names suggest more specific alternatives, but this routing is left to inference rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
references_ofReferences ofAWhat the given work CITES (its outgoing references).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum edges to return per tier (default 100, max 1000). Well-cited works have thousands; the response reports has_more and inferred_total so you can tell a page from the whole answer. | |
| offset | No | How many edges to skip, for paging. Advance by the LIMIT you asked for, not by the number of results you got back — duplicates are removed after the window is taken, so a page can return fewer rows than it consumed. Keep going while has_more is true. | |
| identifier | Yes | DOI, arXiv id, OpenAlex id, or internal claim id | |
| asserted_only | No | If true, restrict to human-signed (asserted) edges. If false (default), return both asserted and machine-inferred edges. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish that the tool is read-only, idempotent, and non-destructive. The description adds no further behavioral context such as pagination behavior, edge types, or response shape; the schema parameter descriptions carry that burden instead. There is no contradiction and the safety profile is covered.
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?
A single, front-loaded sentence conveys the core operation without filler. 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?
The description is sufficient for basic understanding, and the schema richly documents all parameters. However, with no output schema, the description does not explicitly state the return shape beyond 'references,' and the meaning of 'tier' remains unexplained.
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 baseline applies. The description does not amplify or clarify parameter semantics beyond what the input schema already provides in detail.
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 operation: returning what the given work cites, explicitly labeled as 'outgoing references.' This distinguishes it from siblings like what_cites by clarifying directionality.
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 implies when to use the tool—when you need outgoing references of a work—but does not explicitly state conditions or direct the agent to alternatives for incoming citations or other edge types. Usage must be inferred from the phrase 'outgoing references'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
what_citesWhat citesAWorks or claims that CITE the given identifier (incoming citations).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum edges to return per tier (default 100, max 1000). Well-cited works have thousands; the response reports has_more and inferred_total so you can tell a page from the whole answer. | |
| offset | No | How many edges to skip, for paging. Advance by the LIMIT you asked for, not by the number of results you got back — duplicates are removed after the window is taken, so a page can return fewer rows than it consumed. Keep going while has_more is true. | |
| identifier | Yes | DOI, arXiv id, OpenAlex id, or internal claim id | |
| asserted_only | No | If true, restrict to human-signed (asserted) edges. If false (default), return both asserted and machine-inferred edges. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare a read-only, idempotent, non-destructive operation, so the safety profile needs no repetition. The description adds semantic context that results are citing works or claims, but operational behavior such as pagination quirks or inferred totals appears only in the schema, not in the description itself.
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 a single front-loaded sentence that states the core operation immediately and contains no filler. It is concise without sacrificing the essential directional meaning.
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 rich parameter descriptions and safety annotations cover most calling considerations, including paging and asserted/inferred edge filtering. However, there is no output schema, and the description only hints at the response shape through 'works or claims,' so the agent must infer return details from has_more and inferred_total references in the schema.
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 baseline is 3. The tool description provides no additional parameter meaning beyond 'given identifier'; the schema already thoroughly documents limit, offset, identifier formats, and asserted_only.
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: 'Works or claims that CITE the given identifier.' The parenthetical 'incoming citations' explicitly clarifies direction, immediately distinguishing it from outgoing-reference tools and adding meaning beyond the tool name.
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 'incoming citations' phrase implies the intended use case, but the description never explicitly contrasts this tool with siblings like references_of or what_supports, nor states when not to use it. Usage guidance is left entirely to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
what_refutesWhat refutesAEdges asserting or indicating that something REFUTES the given work or claim.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum edges to return per tier (default 100, max 1000). Well-cited works have thousands; the response reports has_more and inferred_total so you can tell a page from the whole answer. | |
| offset | No | How many edges to skip, for paging. Advance by the LIMIT you asked for, not by the number of results you got back — duplicates are removed after the window is taken, so a page can return fewer rows than it consumed. Keep going while has_more is true. | |
| identifier | Yes | DOI, arXiv id, OpenAlex id, or internal claim id | |
| asserted_only | No | If true, restrict to human-signed (asserted) edges. If false (default), return both asserted and machine-inferred edges. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the operation read-only, idempotent, and non-destructive. The description adds meaningful behavioral context by signaling that results include both human-asserted and machine-inferred edges ('asserting or indicating'), which maps to the asserted_only parameter. It does not address edge cases like empty results or rate limits, but those are less critical given the schema's paging details.
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?
A single, front-loaded sentence conveys the tool's core purpose with no filler or repetition of schema details. It earns its place and is easy to scan.
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 simple read-only edge query, the description plus the exhaustive schema is nearly complete. There is no output schema, so the return edge shape is not detailed, but parameter descriptions already mention has_more and inferred_total, covering the key paging behavior an agent needs.
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 all four parameters are already documented with types, defaults, and constraints. The description only reinforces that the identifier refers to a 'work or claim', adding little 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?
Description names a specific resource ('edges') and a specific relation ('REFUTES'), making the tool's purpose unambiguous. It naturally contrasts with sibling what_supports, so an agent can distinguish them without opening schemas.
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 'asserting or indicating that something REFUTES the given work or claim' tells an agent exactly when to use this tool: when looking for refuting evidence. It does not explicitly name alternatives like what_supports or what_cites, but the relation-based semantics makes the selection context clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
what_supportsWhat supportsAEdges asserting or indicating that something SUPPORTS the given work or claim.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum edges to return per tier (default 100, max 1000). Well-cited works have thousands; the response reports has_more and inferred_total so you can tell a page from the whole answer. | |
| offset | No | How many edges to skip, for paging. Advance by the LIMIT you asked for, not by the number of results you got back — duplicates are removed after the window is taken, so a page can return fewer rows than it consumed. Keep going while has_more is true. | |
| identifier | Yes | DOI, arXiv id, OpenAlex id, or internal claim id | |
| asserted_only | No | If true, restrict to human-signed (asserted) edges. If false (default), return both asserted and machine-inferred edges. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive, so no safety caveats are missing. The description adds the asserted-vs-indicating distinction, but otherwise discloses no additional runtime behavior (pagination, truncation, or output shape is left to the 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?
A single front-loaded sentence with every word earning its place. It identifies the entity type, the support relation, and the accepted target without padding.
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 combined definition is usable, and the rich schema descriptions explain paging and filtering, but there is no output schema and the tool description does not describe the edge fields or the 'tier' concept mentioned in the schema. An agent gets enough to call it, but not full clarity on the response.
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 all four parameters are already documented in detail; the description itself adds no parameter-level meaning. The baseline of 3 applies because the schema carries the load.
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 concrete resource ('edges') and the exact relation ('something SUPPORTS the given work or claim'), which clearly separates it from siblings like what_refutes, what_cites, and references_of. No ambiguity about what kind of result the tool returns.
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 implies the use case—retrieve supporting edges for a work or claim—but it never states when to prefer this tool over its siblings or when not to use it. There is no explicit routing to what_refutes or what_cites.
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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