電影影集動畫上映日資料庫

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 the breadth of returned content (dates, rescheduling history, trailers, news) and that queries work across Chinese/English/Japanese, but says nothing about auth needs, ambiguity handling for partial matches, or failure 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?

One dense sentence with the purpose and scope front-loaded and examples at the end. The mid-sentence enumeration is long but every item adds real scope information; nothing is padded.

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 one-parameter lookup with no output schema and no annotations, the description covers what it returns, what input forms are valid, and its single-work scope. The main omission is behavior on ambiguous or partial title matches, which matters given the overlapping lookup_any_title sibling.

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 single 'q' parameter has no schema description (0% coverage), so the description must compensate — and it does, stating that Chinese, English and Japanese titles are all accepted and giving concrete examples ('沙丘3', 'Avengers Doomsday', '薬屋のひとりごと'). This is meaningfully more than the bare schema provides.

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 clear verb+resource ('查單一作品') and enumerates the specific data returned (製作、發行平台、導演、上映時程、預告、新聞), so an agent knows exactly what this tool produces. It implicitly separates itself from list_titles by scoping to a single work, but never addresses the overlapping sibling lookup_any_title.

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?

Usage is implied by '單一作品' versus list-style siblings, and the multilingual examples show valid query forms. However there is no explicit when-to-use versus lookup_any_title, no exclusion for when a title is ambiguous, and no stated alternatives.

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 full behavioral burden. It does not disclose return format, pagination, result ordering, or whether 'upcoming' filtering interacts with the date range. For a list tool with 6 params and no annotations, this is a notable gap.

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 efficient sentence that front-loads the resource and scope, then lists filters. No waste, though enums and parameter mapping could be tightened.

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 6 params, 0% schema coverage, and no annotations or output schema, the description is too thin. It omits the 'upcoming' parameter, does not clarify enum values for type/status, and does not describe the return shape or 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 0%, so the description should compensate. It mentions filter axes at a high level (類型、平台、狀態、日期) but does not map them to specific parameters, does not explain the from/to semantics, and never mentions the 'upcoming' boolean at all.

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 (列出/list) and resource (電影、影集、動畫、劇場版) with scope (2026–2027). It distinguishes itself from get_title/lookup_any_title by being a list operation, but does not explicitly name 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?

The description implies usage by enumerating filter axes (類型、平台、狀態、日期), which signals this is for browsing/filtering. However, it gives no explicit when-to-use vs. get_title, lookup_any_title, or release_calendar.

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, and it does disclose the data source (Wikidata public data), which signals likely coverage/accuracy limits and an implicit read-only nature via 'look up'. It does not describe behavior on missing entries, ambiguity resolution, or result shape.

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 enumerated return fields are the only slightly list-heavy part but they are informative rather than redundant.

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 and no annotations, the description usefully enumerates the returned fields, partially compensating. However the input contract (what 'q' accepts) and ambiguity/error handling remain unexplained for a lookup 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 single parameter 'q' is never explained. The description implies q is a title name but gives no format guidance (native vs English title, Wikidata QID, year disambiguation), which matters for a fuzzy title lookup.

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 (查/look up) and resource (any movie, series, anime) and even the data source (Wikidata) plus the fields returned (release date, director, studio, platform, official site, YouTube). This distinguishes it from narrower siblings like release_calendar or release_countdown, but it never names an alternative to contrast against get_title.

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 when-not-to-use, and no mention of the sibling tools (get_title, list_titles). An agent must infer that this is the broad 'look anything up' tool versus the narrower ones purely from the word 'any'.

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 exist, so the description carries the full behavioral burden, and it does not state whether the month parameter is optional (0 required params suggests a default) or what happens when it is omitted. It discloses scope (includes undated/announced-only works) but nothing about ordering, pagination, or permissions.

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 compact sentence with no filler, front-loaded on the monthly calendar scope. Slightly terse for a description that has to carry meaning on its own, but nothing wastes space.

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 needs to stand alone; it covers what content is returned but omits the behavior of the optional month argument and any ordering/paging expectations. Adequate but with clear gaps for a discovery-style listing 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 coverage is 100% and the single 'month' parameter is self-documented as YYYY-MM. The description's 'by month' phrasing maps to the parameter but adds no format, default, or range detail beyond the schema, so the baseline 3 applies.

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 and scope: a month-based calendar of releases/broadcasts, plus a distinct second category (titles with only an announced period and no fixed date). An agent can tell what content it returns, though the verb is implicit and it does not contrast itself with siblings like release_countdown or schedule_changes.

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?

Usage is only implied: an agent can infer this is the tool for browsing a monthly calendar rather than counting down to a specific title. No explicit when-to-use, when-not-to-use, or alternative routing against release_countdown/schedule_changes is provided.

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 at all, the description carries the full behavioral burden and discloses almost nothing: no timezone handling for the day count, no data source or staleness, no behavior when the title is unrecognized or already released, and no indication the queried title is resolved against a catalog. Only the default fallback ('Avengers: Doomsday') is revealed.

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 short sentence with no padding, and the default value is front-loaded in parentheses. Efficient, though the parenthetical default is arguably more schema/annotation material than description material.

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 an undocumented parameter leaves the agent without enough to call this reliably — it cannot tell what 'q' should contain, what integer or structure comes back, or how it differs from 'release_calendar'.

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 opaque name 'q'. The description never explains that 'q' accepts a title query string, nor what happens if it is omitted (implied default is stated but not tied to the parameter). With low coverage the description should have compensated and does not.

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 computation (days remaining until a work's theatrical release or premiere) and gives a default title, so the resource and output type are inferable. However, it never clarifies what counts as a 'work' (movie only? TV series? games?) and does not distinguish itself from sibling 'release_calendar', which plausibly covers the same domain.

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, no exclusions, and no mention of the closest sibling 'release_calendar' or 'lookup_any_title'. The agent is left to guess whether this returns a single number versus a full schedule.

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, and it does disclose a useful trait beyond the name: every change is accompanied by its source. It implies a read-only listing, but says nothing about ordering, recency window, or what a 'change' record 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 compact sentence with no filler, front-loaded on the resource scope. It is terse to the point of omitting any routing or return-shape detail, which is why it is not a 5.

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 zero-parameter, no-output-schema tool the description covers the essentials of what is returned, but with no annotations and no return schema the agent still lacks ordering, filtering scope, and record-shape information. Adequate but with clear gaps.

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 zero parameters, so there are no parameter semantics to clarify; the baseline of 4 applies. The description appropriately does not waste space describing non-existent 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?

The description names a specific resource-scope — titles with schedule changes (delays, advances, distributor swaps) — and enumerates the change types, so an agent knows what this returns. However, it never states an explicit verb and gives no contrast with siblings like release_calendar or release_countdown, which also concern release timing.

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 prerequisites, and no mention of alternatives. An agent must infer that this is for tracking announced release-date changes rather than upcoming releases, but nothing in the text confirms that.

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