GRIN-scored news for agents: discover by verdict, pull full analysis, traverse extraction graphs.
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Average 4.4/5 across 6 of 6 tools scored.
Each tool serves a distinct purpose: retrieving articles, graphs, related stories, site info, categories, and listing stories. No overlap or ambiguity.
All tools follow a consistent verb_noun pattern (get_*, list_*), making the API predictable and easy to navigate.
With 6 tools, the server is well-scoped for a specialized news analysis API. Not too few, not too many.
Covers core functionality (listing, retrieving, related stories, metadata). Minor gap: no full-text search, but title search suffices for many use cases.
get_articleAFetch one BedrockNews story by id. Returns the transformed article plus its full structured analysis (GRIN scores, extraction graph, key stats, trajectory, what-to-watch). Pass fields:'grin' to get just the analysis payload without the heavy body text. Story ids contain slashes (e.g. 'ledger/2026/apr/06/iran-war-math-doesnt-work') — pass them verbatim.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The story id, verbatim (ids contain slashes) | |
| fields | No | Optional projection: 'grin' for the analysis-only view |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true. Description adds rich detail about return payload (GRIN scores, extraction graph, etc.) and optional projection, providing context beyond 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 succinct sentences: purpose, output details, usage tip. No filler, front-loaded with main action.
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?
No output schema, but description fully explains what is returned (transformed article plus structured analysis). Covers all essential aspects for a fetch 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 already describes both parameters (100% coverage). Description adds practical usage details: id must include slashes, fields='grin' for analysis-only view. Exceeds 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?
Clear verb 'fetch' and resource 'BedrockNews story by id', distinguishes from siblings like get_extraction_graph by specifying it returns the full article plus analysis.
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?
Explicitly advises to pass ids verbatim including slashes, and describes optional fields projection. No explicit when-not, but the sibling names imply alternatives for specific sub-tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_extraction_graphAReturn a story's extraction map as a real graph — nodes + edges data, not a picture. This is the load-bearing artifact for agents: re-render it in any style, or analyze who extracts value from whom. 'Not found' can mean the story has no graph (culture/research modes, or older transforms).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The story id, verbatim (ids contain slashes) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is consistent with the readOnlyHint annotation, describing a read operation. It adds transparency about the 'not found' case meaning no graph exists due to story mode or older transforms, which goes beyond the 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?
The description is concise with three sentences. The first sentence states the action and resource, the second adds context on usage value, and the third clarifies a possible scenario. No unnecessary words.
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 sufficiently complete for a simple retrieval tool with one parameter and readOnlyHint. It explains the output format (nodes+edges, not picture), use case, and a caveat, covering essential context.
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 describes the single parameter 'id' with adequate detail. The description does not add additional semantics beyond what the schema provides, meeting the baseline for 100% coverage.
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 purpose: return a story's extraction map as a real graph (nodes + edges data, not a picture). It distinguishes from siblings like get_article by specifying the resource and data format.
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 explains that this is a 'load-bearing artifact' for agents to re-render or analyze value extraction, implying usage scenarios. It also notes that 'not found' may indicate no graph exists, but does not explicitly contrast with alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_site_infoABedrockNews metadata: what the site is, how the GRIN/CLAIMS/NOVEL frameworks work, terms of use + attribution, and every machine-readable surface. Also returns the full capability map (every tool, prompt, and resource) — call this first.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description aligns perfectly. It adds significant value by specifying exactly what the tool returns: site metadata, framework explanations, terms of use, and a capability map. There is 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?
The description is a single sentence that packs essential information: what the tool does, what it returns, and when to call it. It is front-loaded with the key purpose and is concise with no wasted words.
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 no parameters and no output schema, the description fully informs the agent about the tool's purpose and return content. It covers the key aspects: what metadata is returned and the instruction to call it first. Completeness is high for a simple discovery 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 zero parameters, so per guidelines the baseline is 4. The description does not need to add parameter information. It correctly describes the output without referencing parameters.
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 that the tool returns 'BedrockNews metadata' and 'the full capability map (every tool, prompt, and resource)'. It distinguishes itself from sibling tools like get_article and list_categories by focusing on overarching site info rather than specific articles or lists.
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 'call this first', providing a clear usage directive. While it does not explicitly state when not to use it or list alternatives, the instruction to use it first is strong guidance for an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_categoriesAThe BedrockNews category taxonomy: ids (valid values for list_stories' category filter), display names, and which editorial framework each category runs (grin | culture | auto).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only. The description adds value by detailing exactly what data is returned (ids, display names, frameworks). There is no contradiction with annotations, and the additional context enhances understanding of the tool's behavior.
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, well-structured sentence that immediately identifies the resource (BedrockNews category taxonomy) and lists the key outputs. Every part of the sentence contributes value, with no wasted words.
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 no output schema and no parameters, the description adequately explains what the tool returns. It ties into the sibling tool list_stories, providing useful context. Minor improvement could be explicit mention of list format, but it's sufficient for most agents.
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 no parameters, so schema coverage is 100%. According to guidelines, baseline is 4 for zero parameters. The description does not need to add parameter meaning, and it correctly avoids redundant information.
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 tool returns the BedrockNews category taxonomy, including ids, display names, and editorial frameworks. It explicitly distinguishes itself from sibling tools by noting that the ids are valid values for list_stories, making the purpose specific and actionable.
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 implicitly guides usage by linking the returned ids to list_stories' category filter, suggesting this tool is a prerequisite for filtering stories. While it doesn't explicitly state when not to use, the context is clear enough for typical scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_storiesADiscover BedrockNews stories with GRIN-aware filters. Filter by verdict ('extractive' | 'mixed' | 'generative'), plumb range (0-100 analytical-clarity score), editorialMode ('grin' news/politics | 'culture' | 'research' | 'ledger'), category (see list_categories), date window (since/before, ISO 8601), or a title search (substring match on titles, not full text). Sorted newest first; paginated via cursor. Returns compact story briefs — use get_article for full analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 15, max 50) | |
| query | No | Optional title search (substring match) | |
| since | No | Only stories published at/after this ISO 8601 date | |
| before | No | Only stories published before this ISO 8601 date | |
| cursor | No | Opaque pagination cursor from a previous call | |
| verdict | No | GRIN verdict filter, derived from grinScores.extractive | |
| category | No | Category id filter (e.g. 'politics', 'research') | |
| plumbMax | No | Maximum plumb (0-100) | |
| plumbMin | No | Minimum plumb (0-100) | |
| editorialMode | No | Filter to one editorial framework |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, and the description confirms read-only behavior ('discover', 'returns compact briefs'). It also discloses sorting (newest first) and pagination via cursor. No contradictions or missing critical behavioral 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?
The description is extremely concise (two sentences), front-loaded with the tool's main purpose, and every sentence adds necessary guidance 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?
The tool has 10 parameters (all optional) and no output schema. The description covers filter types, sorting, pagination, and briefly mentions return format ('compact story briefs'). While it could detail returned fields, it is sufficiently complete for a list endpoint.
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%, but the description adds substantial semantic value: explains verdict as GRIN-derived, plumb as analytical-clarity score (0-100), editorialMode options, category referencing list_categories, date ISO 8601, and title as substring match on titles 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 clearly states the tool is for discovering BedrockNews stories with GRIN-aware filters, listing specific filter types, sorting, and pagination. It distinguishes from get_article by directing users to that tool for full analysis.
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 explicit context for when to use this tool (discover stories with filters) and mentions get_article as an alternative for full analysis. However, it does not explicitly state when not to use this tool, though the purpose is clear enough.
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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