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

With no annotations, the description carries the burden of behavioral disclosure. It explains that patch notes carry dates and can be used to correlate with rating changes, and that press items are third-party articles. However, it doesn't disclose potential limitations like pagination, rate limits, or whether 'all' kind returns both types in a specific order. The description adds some behavioral context but not comprehensive.

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, front-loading the core purpose and then adding useful detail about the two content types. Every sentence earns its place, and the structure is clear. It could be slightly more concise, but it's efficient and readable.

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 tool has 4 parameters, no output schema, and no annotations, the description provides moderate context. It explains the two kinds of news and their use case, but doesn't cover return format, pagination, or how 'all' behaves. For a news-fetching tool, an agent might need more detail on output structure, but the description covers the essential purpose and filtering logic.

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 only 25% (only 'since' has a description). The tool description explains the meaning of 'kind' by distinguishing patches and press, which adds value beyond the enum values. However, it doesn't clarify 'appid' or 'limit' semantics beyond what the schema provides. The description partially compensates for the low coverage but leaves gaps.

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 retrieves Steam news for a game, distinguishing developer announcements (patch notes) from press articles. It names the resource (game news) and the two content types, which helps an agent understand the tool's purpose. However, it doesn't explicitly differentiate from sibling tools like search_articles, though the distinction between game-specific news and general articles is implied.

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 context on when to use the tool: to find patch notes near a rating change or to access press items. It implies the tool is for game-specific news, which differentiates it from search_articles, but it doesn't explicitly state when not to use it or name alternatives. The guidance is useful but not fully explicit.

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 no annotations, the description carries the burden and it discloses a non-obvious limitation: old dates are not accessible and fail with a clear message. It does not describe return shape or ordering, but for a read-only reviews tool the key behavioral caveat 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?

Three sentences with the main purpose first, followed by the critical limitation and the alternative. Every sentence adds information and there is 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?

The description, combined with a schema that documents most parameters, gives an agent enough to call the tool correctly: required appid, optional filters, and the historical limitation. A return-format note would be a nice addition, but the tool name and title make the output self-evident.

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 67%, and the description adds conceptual meaning by grouping filters into 'date window', 'sentiment', and 'players with real time', mapping to since/until, voted_up, and min_playtime_hours. It does not discuss limit, but the schema and tool context make it self-explanatory.

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 the resource ('Reviews for a game') and the three optional filter dimensions (date window, sentiment, player time) with a clear verb implied by the tool name. It also names get_review_timeline as a different tool, so it is easy to distinguish from siblings.

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 explicitly says only recent windows can be read and gives a direct routing rule: use get_review_timeline for old history. This tells the agent when to call this tool and when not to.

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?

There are no annotations, so the description carries the burden. It discloses output granularity, time range, full-history coverage, and relative cost, which is substantial. It does not mention auth, rate limits, or exact response structure, but for a simple read-only aggregation tool this is reasonable.

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 tightly packed sentences: the first states what the tool returns, the second explains why it is the right choice. No filler or repeated schema 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 one simple integer parameter and no output schema, the description gives enough about the returned data and the tool's advantages to guide correct use. It omits explicit appid guidance and response encoding details, but those are minor for this 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 description coverage is 0% and the description never mentions appid or explains how to supply it. The only connection is 'for a game', which weakly implies the appid parameter. The parameter name is self-explanatory, but the description adds no real semantic value 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?

The description names a specific resource (review timeline for a game) and the exact data returned (monthly positive/negative counts, daily last-30-days). It also distinguishes itself from get_reviews, so an agent can tell which tool to pick.

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 explicitly says this is the way to find when a rating moved and contrasts itself with get_reviews by noting it is cheap and covers all history. It does not fully spell out the opposite case ('use get_reviews when you need individual review content'), but the comparison gives clear 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?

There are no annotations at all, so the description carries the full burden of behavioral disclosure. It explains the data source and that the search is over collected press articles, but it does not disclose what the tool returns, how results are ordered, whether results are paginated, or what 'collected from outlet feeds' means in terms of recency or coverage. The phrase 'right now' hints at freshness but does not define it.

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. The first sentence front-loads the core action and resource, and the second sentence adds a scope distinction that helps differentiate this tool. Every clause 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 tool has 3 parameters, no annotations, low schema coverage, and no output schema, so the description needs to do substantial explanatory work to be complete. It explains the search domain but never mentions what the agent will receive (the result shape), how to control result volume (limit), or how to anchor the recency of the search (since_days). As a result, an agent has to guess or rely on external knowledge to call the tool optimally.

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 only 33% (only since_days has a description), so the description must compensate for the undocumented parameters. The description conveys that the search is full-text and about games or topics, which gives some semantic meaning to the query parameter, but it says nothing about limit or since_days and does not help an agent decide how to set 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 states a specific verb and resource: full-text search over gaming press articles collected from outlet feeds. It also gives the important scope cue that it covers the industry generally rather than Steam-specific data. It does not name sibling tools explicitly, and the phrase 'Steam tools' only vaguely differentiates it from siblings like get_game_news or search_games.

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 this is useful—the industry press generally as opposed to Steam tools—and explains that it answers what is being written about a game or topic right now. However, it never names sibling tools or explicitly states when not to use this tool (e.g., when you need Steam review timelines, use get_review_timeline), so it remains more implied than explicit.

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 no annotations provided, the description carries the behavioral disclosure burden. It usefully discloses prefix matching, typo sensitivity, and language-dependent title behavior. It does not describe output shape, rate limits, or auth, but for a simple search tool the disclosed behaviors are the most decision-relevant.

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 short sentences each add distinct value: purpose, matching rules, and language behavior. The critical 'appid needed by other tools' fact is front-loaded, and there is no redundant 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?

Given there is no output schema, the description communicates the core return purpose (appid) and matching behavior. It does not specify whether multiple results are returned or how limit affects output, but for a straightforward search tool the essential invocation context is present.

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 67%, covering query and language. The description adds behavioral meaning to query semantics by specifying prefix matching and typo behavior, and enriches language semantics by noting Russian searches return Russian titles. The limit parameter is left to the schema, but the added parameter context is valuable.

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 finds Steam games by name and returns appid, explicitly noting this appid is needed by other tools. This distinguishes it from sibling tools like get_reviews or search_articles, making its purpose unmistakable.

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 this is the entry-point tool for anything requiring a Steam appid, with concrete matching behavior (prefix, no typos, language-dependent results). It does not explicitly name alternatives or when-not-to-use, but the context and sibling list make the usage clear enough.

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