SkimNews

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds real behavioral context: dossiers are permanent, built only for repeatedly covered entities, and counts span a 60-day window.

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 tight sentences: what the dossier is, what it returns, and when to use it, followed by the slug form. Front-loaded and every sentence carries information.

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, return values need not be detailed, and the description is nonetheless explicit about contents. Minor gap: it doesn't address the empty default on slug or ambiguous/unknown entity slugs.

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% and the single slug parameter is already documented there, so the schema does the heavy lifting. The description's slug examples duplicate the schema examples and add no new syntax or format guidance, making this the baseline 3.

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?

States a specific resource (an entity dossier) and enumerates exactly what it returns: 3-sentence status, 60-day mention/source counts, recent coverage, related entities. This clearly separates it from the story-centric siblings (get_story_detail, get_top_stories, search_stories).

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?

Gives concrete trigger phrasings ('what has SkimNews covered about X', 'what's the latest on X') and scopes them to trackable entities, which is clear context. It never says when not to use it or names a sibling as the alternative, so it stops short of a 5.

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 readOnly, idempotent, openWorld, non-destructive, so the safety profile is covered. The description adds genuine context by revealing the scope of the returned editorial content and the citation use case, but says nothing about rate limits, auth, or how missing/ambiguous identifiers are handled.

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, front-loaded with what the tool returns and then when to reach for it. The return-value enumeration is long but each item is distinct payload content, so it earns its space; only minor trimming would improve it.

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, return structure need not be spelled out, yet the description still orients the agent on payload richness and the identifier formats accepted. Nothing needed to call this single-parameter read 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% and the single parameter is self-documented, so the baseline is 3. The description goes beyond it by giving a concrete id example ('46b45d01') and confirming the canonical skimnews.com URL and slug forms are interchangable inputs.

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?

States a specific verb+resource ('full SkimNews treatment of one story') and enumerates the payload (summary, why-it-matters, bullets, editorial take, entities, taxonomy, canonical URL), which cleanly separates it from the list-returning siblings get_top_stories and search_stories.

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?

Gives an explicit trigger and ordering: 'Use after get_top_stories or search_stories when a story needs detail or accurate citation.' It names the alternatives and the condition selecting this tool, though it stops short of stating when not to use it.

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 openWorldHint, so the safety profile is covered. The description adds that results include summaries plus canonical URLs, which is mildly useful context, but with an output schema present it adds little behavioral disclosure beyond the structured data.

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 tight sentences, front-loaded with the what, then usage intents, then return shape and categories. Nothing is padding, though the return-shape sentence is partly redundant given an output schema exists.

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 annotations covering safety, an output schema covering returns, and full parameter documentation, the description only needs to add routing and category semantics, which it does. It is complete enough to call correctly, lacking only explicit alternative-tool guidance.

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, but the description adds real value: the category field's schema is an unconstrained anyOf string with no enum, and the description supplies the authoritative list of seven beats. It does not explain the limit parameter's interaction with categories, keeping it from a 5.

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?

States a specific verb and resource ('Today's top SkimNews stories'), plus scope ('today') and the optional beat narrowing. An agent can distinguish it from get_story_detail (single story) and search_stories (query-driven) without opening the schema.

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 maps the tool to user intents: "what's happening today" / "today's news" / "latest in <beat>". That is clear when-to-use guidance, but it never names an alternative (search_stories) or a when-not condition, so it stops short of full routing 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 declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so safety is covered structurally. The description adds genuinely useful behavior beyond that: results are relevance-ranked, they contain summaries plus canonical URLs, and an empty list has a definite meaning the agent must not paper over. It omits nothing important, though it doesn't discuss latency or result-count behavior beyond 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?

Three tightly written sentences: capability and scope first, then differentiation from today-only lookup, then the empty-result contract. Every sentence carries a distinct, load-bearing instruction with no filler.

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, the description needn't enumerate return fields, and it still summarizes them (summaries plus canonical URLs). Combined with rich annotations and 100% schema coverage, all four parameters accounted for, and the failure-mode instruction included, an agent has everything needed to call this 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 description coverage is 100%, so days, limit, category, and query are all self-documented in the schema, which sets the baseline at 3. The description echoes the query semantics ('topic, theme, or news event') but adds no format, syntax, or interaction guidance for the filter parameters beyond what the schema already states.

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 (semantically search) plus resource (SkimNews' archive of 47,000+ summarised stories) and scope (by topic, theme, or news event, ranked by relevance). It explicitly contrasts with the sibling-driven default of only-today coverage, so an agent can distinguish it from get_top_stories without opening a schema.

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 names when to reach for this tool ('find coverage of a subject across SkimNews' history rather than only today') and prescribes the correct behavior on failure ('an empty result list means SkimNews has not covered that topic — say so rather than substituting unrelated stories'). That is an explicit when-to-use plus an exclusion rule, not just implied context.

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