遊戲發售日與預告片資料庫

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

No annotations are provided, so the description carries the full burden. It usefully discloses that each change record carries the original announcement link, but says nothing about scope (all games? a time window?), sort order, or freshness, which an agent would want before calling.

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 spends no words on filler. It states the scope first and the payload second, which is the right ordering.

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 parameterless tool with no output schema, the description must explain what comes back, and it partly does (change entries with announcement links). It still omits scope and ordering, so an agent cannot fully predict the result set.

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 no parameters, so there is nothing for the description to disambiguate. Baseline 4 applies for a zero-parameter definition.

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 and scope: games whose official release schedule changed (delayed or advanced). This is clearly distinct from release_calendar and release_countdown, though it never names those siblings explicitly. The function is understandable at a glance.

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 when-to-use or when-not-to-use guidance is given. It does not explain how this differs in practice from release_calendar, release_countdown, or get_game, leaving the agent to infer that this is the historical/changelog view.

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 full disclosure burden. It does useful work by explaining what each ranking is based on (anticipation votes vs. star ratings) and what fields accompany entries (release date, platform, trailer link), effectively pre-describing return content. However, it says nothing about ordering rules, pagination, or any access constraints.

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 dense sentence that front-loads the core resource and packs the ranking basis and included fields without filler. Slightly compressed but 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?

No output schema and no annotations, so the description justifiably covers returned fields. But it omits usage context and leaves the 'limit' parameter unexplained, leaving gaps for a simple read tool with a 50%-covered 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 coverage is 50%: the 'list' enum has its own description and the description's two ranking modes roughly map to it. But 'limit' is undocumented in both schema and description, so its behavior (count, page size?) is unaddressed. Baseline 3 is appropriate given partial 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 states a specific resource (game hype rankings) with two well-defined modes: unreleased games ranked by member anticipation votes, and released games ranked by 1-5 star ratings. An agent can tell this is a ranking tool, distinct from release_calendar or official_game_trailers, though it never explicitly names or contrasts with those 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?

There is no explicit when-to-use guidance or routing to alternatives. The description implies the tool is for rankings, but an agent choosing between this, release_calendar, and official_game_trailers gets no conditions from the text.

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?

No annotations are provided, so the description carries the full burden. It implies a read-only lookup via '查' but does not explicitly state read-only safety, auth requirements, rate limits, or error behavior. It mainly enumerates returned fields rather than behavioral traits.

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?

One compact sentence front-loads the core action and then lists returned data and parameter notes without filler. Every clause contributes useful 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?

For a simple single-game lookup with no output schema, the description usefully lists the returned data fields and parameter language support. However, it omits guidance on when to choose this tool over siblings like lookup_any_game or delay_history, and it does not disclose any behavioral traits since annotations are absent.

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 0% schema description coverage for the single required parameter q, the description compensates by stating that both Chinese and English names are accepted and giving examples (GTA VI, 俠盜獵車手VI). This adds clear semantic guidance for the parameter beyond the bare schema type.

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 (查單一遊戲) and enumerates the data returned, which helps distinguish it from list_games. However, it does not explicitly differentiate from lookup_any_game or delay_history, so sibling disambiguation is left to inference.

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?

Provides no explicit when-to-use or when-not-to-use guidance, and does not name alternatives among siblings (lookup_any_game, list_games). The only usage hint is that Chinese or English names are accepted, which is parameter-level, not tool-selection 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?

No annotations are provided, so the description carries the full burden. It discloses returned fields (announcement date, release date, status) and that filtering is possible, but omits pagination, result limits, explicit read-only assurance, and auth/rate-limit behavior. Minimum viable but with gaps.

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?

One front-loaded sentence with semicolons, covering scope, fields, and filters without filler. Appropriately sized for the tool's purpose.

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 annotations, no output schema, and 0% parameter description coverage. The description gives scope and some returned fields, but is incomplete for a 5-parameter list tool lacking return format, pagination, and parameter details.

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 0% for 5 parameters. The description mentions platform, status, and date filters, but leaves 'upcoming' undocumented and does not specify date formats or status enum meanings. It only partially compensates for the missing schema descriptions.

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 states a specific verb '列出' (list) and resource '重點遊戲' with scope (2026–2027) and platforms. It does not explicitly distinguish from siblings such as release_calendar or lookup_any_game, so it is clear but not sibling-differentiating.

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 says the list can be filtered by platform, status, and date, implying use for filtered game listings. However, it gives no when-to-use guidance relative to siblings like get_game or release_calendar, and no exclusions.

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?

No annotations are provided, so the description carries the full burden. It does disclose the data source (Wikidata public data), which reasonably implies a read-only, unauthenticated lookup and explains why results may cover arbitrary games, but it says nothing about latency, rate limits, or what happens when a title is not found.

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 also enumerates the returned fields. No wasted words, though the enumerated field list could be read as pre-empting output 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?

With no annotations and no output schema, the description usefully lists the returned data (release date, platforms, developer, website, YouTube) which compensates for the missing output schema. It remains incomplete on parameter semantics and on its relationship to sibling tools.

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 0% and the single parameter is the cryptic name 'q'. The description's phrasing about looking up 'any game' weakly implies q is a game name, but it never clarifies whether q accepts a title string, a Wikidata Q-ID, or both — a meaningful gap for a lookup tool.

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 verb (look up) and resource (any game) and identifies the data source (Wikidata public data), which distinguishes it somewhat from local-database siblings like get_game and list_games. However, it never names those siblings explicitly, so an agent must infer which tool is appropriate.

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 when-to-use guidance is given. The phrase 'any game' hints that this is for arbitrary titles outside the curated catalog, but the description never states when to prefer this over get_game or list_games, nor any prerequisites.

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?

No annotations are provided, so the description must carry the full behavioral burden. It states that content comes from official YouTube channels and is the latest, but omits return format, pagination behavior, ordering, authentication needs, and how the limit parameter behaves.

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 resource first, then sources and filters. It is dense but not wasteful, though the long company list could be considered slightly verbose.

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/list tool with no output schema and no annotations, the description should ideally say what is returned and how the limit parameter works. It covers content and filtering adequately but leaves gaps around output format and optional parameter behavior.

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%, with enum descriptions already present for group and device. The description adds some value by listing Japanese companies for the 'jp' group and restating device filters, but it does not explain the 'limit' parameter or fully clarify all group values such as 'west'.

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 identifies the resource: latest game trailers and PVs from official YouTube channels, with a list of sources and filterable device types. It does not mention any sibling tools or distinguish itself from release_calendar or game_hype_ranking, but the purpose is specific enough for an agent to understand what 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 provides no explicit when-to-use guidance or alternatives. Usage is only implied by the content (latest trailers/PVs), and there is no indication of when to choose this over other game-related tools.

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?

No annotations are provided, so the description carries the full behavioral burden. It does disclose the returned content fields (headcount, Taiwan-time start, voice requirement, sign-up link), which is genuine value, but it says nothing about read-only nature, auth needs, pagination, or result freshness for an openly listed feed.

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 no filler. The dense field enumeration is slightly packed but each item earns its place by telling the agent what comes back.

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 no output schema, the description usefully enumerates return fields, which covers part of the completeness requirement. However, it leaves usage routing and the platform filter's meaning unaddressed, so an agent gets a workable but not fully rounded picture.

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 50%: 'game' has a description (遊戲名稱關鍵字) while 'platform' is only an enum without prose. The description references 遊戲 and 平台 as content fields, implying they act as filters, but adds no matching syntax or semantics beyond the schema, so it neither compensates for the gap nor misleads.

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 and scope: open game LFG posts for Taiwanese players, enumerating the content carried (game, platform, headcount, start time, playstyle, voice, sign-up link). It is clear what the tool returns, but it never names a verb like 'list/查詢' and does not distinguish itself from the sibling open_game_trades or list_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?

There is no when-to-use guidance, no exclusions, and no mention of alternatives such as open_game_trades or list_games. The agent must infer that this is the browse tool for open recruitment posts without any explicit routing signal.

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 full burden of behavioral disclosure but does little beyond listing data categories. It doesn't specify whether this is a live listing search, how results are paginated, or expected behavior like default sorting. The only implicit behavior is that listings include links.

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 compact sentence that front-loads the key concept (game swap listings by Taiwanese players) and lists relevant features. It wastes little space, though it could be clearer.

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 absence of annotations, no output schema, and only implied usage, the description is incomplete. For a search tool with two optional parameters, an agent needs more detail about what the tool returns, how to interpret results, and how it relates to other game-related tools.

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 50% (the 'q' parameter is documented in the schema, but the 'platform' enum is self-explanatory). The description mentions fields like 'platform' and 'location' that map to the listing content rather than input parameters, adding minimal value over the schema. Baseline 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 is a Chinese-language tagline that names the resource (game swap listings) but is vague about the actual action — it doesn't use a clear verb like '列出' (list) and reads more like a data summary than a tool definition. It does not explicitly distinguish itself from sibling tools like get_game or list_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?

There is no explicit guidance on when to use this tool vs alternatives like list_games or get_game. The description implies it's for browsing trade listings but provides no conditions, prerequisites, or exclusions.

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?

No annotations are provided, so the description carries the full burden. It adds useful behavioral context by stating the output includes undetermined titles, but it omits how the optional month parameter behaves when omitted, whether results are paginated, or what the return structure looks like.

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 sentence with no wasted words, front-loading the primary resource (monthly release calendar) and then the secondary inclusion (undetermined titles).

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 tool with one optional parameter and no output schema, the description covers the main output but fails to specify what happens if month is omitted, which is an important gap given the optional parameter.

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 month format YYYY-MM is already documented in the schema. The description reinforces the by-month grouping but adds no syntax, default, or requiredness details beyond that 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 clearly identifies the resource: a game release calendar organized by month, plus titles that only have an announced period. It does not explicitly differentiate itself from siblings like release_countdown or list_games, but the scope is clear enough to infer.

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?

There is no guidance on when to use this tool versus alternatives such as release_countdown or list_games, nor any mention of prerequisites or exclusions. Usage 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.

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

No annotations are provided, so the description carries the full burden. It does disclose one real behavioral trait not present in the schema: the default argument value (GTA VI). However, it says nothing about the read-only nature, how the game name in 'q' is resolved, or what happens on an unknown game.

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 no filler or redundancy. It is on the terse side but nothing is wasted.

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 no annotations and no output schema, the description leaves the return shape unexplained (e.g., an integer day count) and does not describe game-name resolution or failure behavior. It covers the core purpose but not enough for an agent to call it with full confidence.

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 0% — the single parameter 'q' has no type description. The description partially compensates by implying 'q' is a game identifier and that omitting it defaults to GTA VI, but it does not clarify whether 'q' expects a title, slug, or ID.

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 computation ('距離遊戲發售還有幾天' = days remaining until a game's release) and identifies the default subject (GTA VI). An agent can distinguish this from siblings like release_calendar (a listing of release dates) or get_game (game metadata), though the differentiation is implicit rather than stated.

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?

There is no guidance on when to use this tool versus release_calendar, get_game, or lookup_any_game, and no statement of prerequisites or exclusions. Usage must be inferred entirely from the scope of the sentence.

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 full behavioral burden. It does disclose useful traits: the data source (Steam Store, Taiwan region) and a 6-hour sync cadence, which tells the agent the data may be stale by up to six hours. It does not state auth requirements, whether the operation is read-only, or how the result set is bounded.

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 sentence front-loads the identity of the ranking, then the returned fields, then the refresh cadence. Dense but every clause adds information; 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?

Listing the returned fields partly compensates for the absent output schema, and the region and sync cadence give useful framing. However, the sole input parameter is undocumented and no output schema exists, so an agent still lacks the full picture for correct invocation.

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 single parameter 'limit' is never mentioned in the description, so there is no documented meaning, default, or maximum for it. The description only covers returned fields, not the input, leaving the agent to guess what limit controls.

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 and scope: the Steam Store 'wishlist popular' upcoming-games ranking for the Taiwan region, and enumerates the returned fields. This is clearly distinct from a generic release list, though it never names which sibling (e.g. game_hype_ranking, release_calendar) it is not.

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?

There is no statement of when to choose this tool over game_hype_ranking, release_calendar, or release_countdown, and no exclusions or prerequisites. Usage is only inferable from the tool name and the phrase '即將推出' (upcoming).

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