ottasia

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open world). The description adds non-obvious behavioral detail beyond that: the week-scoped freshness window, and the important asymmetry that new-episode series are only included for English, Korean and Japanese/anime. It does not describe result volume or ordering beyond the limit parameter.

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 core scope statement is front-loaded in the first sentence, followed by example queries and then parameter semantics. The language enumeration is somewhat long but earns its place as a non-enumerated accepted-value list; no sentence is pure 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 0 required parameters, no output schema and an open-world read tool, the description covers the essentials: what is returned conceptually (just-arrived films and shows, plus new-episode series for a subset of languages), along with all three parameter behaviors and defaults. Return ordering and pagination are unspecified, a minor gap for a capped list 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%, so the baseline is 3, but the description materially supplements the schema for 'language': it lists accepted names (Hindi, Telugu, Bangla, etc.), the special values 'anime' and 'K-drama', and the omit-for-default rule, none of which appear as enums in the schema. This compensates for the absence of enum constraints.

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 (List) and resource (what is new on streaming this week) scoped by language and country, which is far more specific than the tool name alone. It does not, however, address its closest sibling 'whats_new_on', leaving a real risk of ambiguity between the two for an agent choosing between them.

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 grounds usage in concrete example queries ('new Telugu movies on OTT this week', 'new anime this week in India') and explicitly states the default behavior (omit language for the country's main language). It stops short of stating when to prefer this over 'whats_new_on' or 'search_titles', so no exclusion guidance 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?

Annotations already declare readOnlyHint, idempotentHint, and non-destructive. Description adds context: returns multiple candidates, includes year/type/overview, and country-aware link, enhancing understanding 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?

Two paragraphs, front-loaded with purpose, then usage guidance. Every sentence is informative with no redundancy or fluff.

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 3 parameters, no output schema, and sibling tools, the description covers purpose, usage, parameter details, and return value, making it fully informative for selecting and invoking the 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 100%, and description adds valuable context: for q it supports multiple languages, for limit and country it explains defaults and purpose of the country parameter.

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 clearly states it searches OTTASIA's catalog for movies or TV shows by name, returns candidates with year, type, overview, and country-aware link, and distinguishes from where_to_watch.

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 specifies when to use ('find me X' or ambiguous queries) and when not to use (use where_to_watch for specific title and country), providing clear decision criteria.

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, openWorldHint, idempotentHint true, and destructiveHint false. The description adds that it returns a list with brief overviews and links, but does not reveal additional behavioral traits beyond what annotations imply. With good annotation coverage, the description adds moderate value.

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 well-structured with the purpose front-loaded, followed by usage examples, parameter lists, and output notes. It is informative but could be slightly more concise without losing clarity.

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 three parameters and no output schema, the description covers input defaults, valid values, output format (list with overviews+links), and usage context with sibling tool pairing, making it fully complete for agent 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 coverage is 100% with parameter descriptions. The description adds extra context by listing example provider slugs, explaining country codes, and noting defaults (limit default 15, country default IN), which aids the agent 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 clearly states the verb 'list' and the resource 'latest movies and TV shows recently added' with specific scoping to a streaming service and country. It distinguishes from sibling tools like search_titles and where_to_watch.

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 usage examples (e.g., 'what's new on Netflix in India'), lists common provider slugs and country codes, and advises pairing with where_to_watch for details, guiding the agent on when and how to use the tool.

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, non-destructive and openWorld, so safety is covered. The description adds genuine behavioral context beyond that: it explains the two branches of behavior (returns services if already streaming, otherwise a predicted date from historical gaps with a confidence level) and that an alert-setup link is returned. It stops short of noting auth needs or prediction caveats/error cases, so not a 5.

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 definition is front-loaded with the use case in the opening sentence, then covers return behavior, then the sibling routing rule. Each sentence earns its place, though the quoted-question opener and the compound second sentence are slightly dense rather than maximally tight.

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 carries the return-value burden well: it explains both outcome branches (services vs. predicted date with confidence), the alert link, and the market scope. Combined with annotations covering the safety profile and a fully-described 2-parameter schema, 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% — both title and country (with ISO examples and the IN default) are documented in the schema. The description only alludes to them implicitly, adding no format or edge-case 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 the exact question it answers ('when is <movie> coming to OTT / Netflix / Prime in <country>') and scopes it to OTTASIA's Asian, Middle Eastern and diaspora markets. It clearly distinguishes itself from where_to_watch by framing itself as the 'WHEN' tool rather than the availability tool.

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 final line gives an explicit routing rule: 'Use where_to_watch for plain availability questions; use this when the user asks WHEN.' This names the alternative tool and the exact condition that selects it, leaving nothing 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?

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, clearly indicating safety. The description adds value by detailing the output (matched title, year, provider list grouped by category, a link) but does not explicitly reaffirm the idempotent or open-world nature. With annotations covering safety, the description provides moderate additional context.

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 at about 10 sentences, front-loads the purpose, and uses a list for markets and providers. It is well-structured and informative without excessive verbosity, though it could be slightly shorter.

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 only 2 parameters with full schema coverage, no output schema, and the presence of annotations, the description provides sufficient context: output structure, example providers, and a link for more details. It does not cover error cases (e.g., title not found), but overall it is complete enough for its complexity.

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?

Input schema coverage is 100%, so baseline is 3. The description adds meaningful extra information: title can be 'English, romanized, or original-language', with examples; for country, it lists the 30 codes and notes default to IN. This goes beyond the schema description, justifying a 4.

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's purpose: 'Find which streaming services carry a specific movie or TV show in a specific Asian or Middle Eastern country.' It specifies the scope (30 markets) and provides examples of streaming services. It implicitly distinguishes from siblings like 'search_titles' and 'whats_new_on' by focusing on availability queries.

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 'Use this tool whenever a user asks "where can I watch X in Y" for any of these 30 markets' and lists the markets. It also says 'Best for queries about availability on...' which gives context. However, it does not mention when not to use it or differentiate from sibling tools, so a 4 is appropriate.

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