Rivioo

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

Annotations already declare this is a safe, idempotent, open-world read, so the bar is lower. The description still adds real context beyond them: it is free, it 'delivers no reviews' (steering review needs elsewhere), and the country influences downstream Google Play review languages.

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?

Four compact sentences, front-loaded with purpose and scope before return values and usage rules. No filler; even the terse 'Free; delivers no reviews' carries decision-relevant 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 fully documented, yet the description still summarizes them. Purpose, alternatives, defaults, and cost are all covered, leaving nothing an agent needs to call it 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 coverage is 100%, so baseline is 3, but the description adds meaning the schema lacks: omitting store searches both stores (no default is documented in the enum) and country's downstream effect on Google Play review languages. Minor gap only in that query syntax/keyword behavior isn't elaborated.

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?

Opens with a specific verb (Search) plus resources (App Store, Google Play) and scope (by name, one storefront country), which cleanly separates it from the review-oriented siblings rivioo_get_reviews and rivioo_search_reviews. It also names the returned fields (app_id per store, developer, rating, store links).

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 routes the agent: 'Use it for apps that are not in rivioo_my_apps', with a sibling named as the alternative. It also tells the agent to ask the user for the unknown country and that omitting store searches both stores, covering the main path and edge case.

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 cover the safe-read profile, and the description still adds substantial behavior: per-review quota cost (one per review per 30 days, free on re-read), App Store per-country vs Google Play per-language-from-all-countries semantics, and conditional url availability. This is exactly the context annotations cannot convey.

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?

Front-loaded with purpose and the sibling distinction, and nearly every sentence carries non-obvious information (quota, platform semantics, pagination). It is dense and runs long, though, with several ideas packed per sentence that bullet points would have surfaced faster.

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 14-parameter tool with an output schema, the description covers everything an agent needs: two input modes, pagination contract, platform scoping, quota economics, and response_format effects. Nothing material is left to inference.

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 93%, so the schema carries most parameter meaning (baseline 3). The description adds value above that base: review_ids should come from rivioo_search_reviews, next_cursor must be passed with the same arguments, and response_format's concise vs detailed field lists are spelled out.

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 (returns a page of full reviews of one app) and immediately distinguishes itself from rivioo_review_stats with 'reviews, not counts'. The sibling routing sentence makes the boundary crisp without opening any other 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?

Explicit when-to-use: use rivioo_search_reviews to count theme mentions, use this to read full reviews. It also names the two operating modes (review_ids for known reviews vs a window with filters for newest-first) and how to page with next_cursor using the same arguments.

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 closed-world, so the safety profile is covered. The description adds value the annotations cannot: cost ('Free'), output scope ('delivers no reviews'), and the behavioral effect of default country on Google Play review language selection.

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, front-loaded with the core action, then routing, then the cost/scope caveat. Every clause carries distinct information and 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?

An output schema exists, so return-value detail in the description is a bonus rather than a requirement, and the annotations cover safety. Combined with the routing cues and the cost note, an agent has everything needed to call this correctly and to place it in the workflow.

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 the baseline is 4 and there is nothing for the description to disambiguate. The mention of 'default country' concerns returned data rather than an input, so it neither helps nor hurts parameter understanding.

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 ('List the apps this Rivioo user saved') and enumerates the returned fields (store, app_id, default country), so the agent knows exactly what this yields. It also implicitly separates itself from rivioo_find_app by framing the scope as the user's saved list rather than a lookup, and names the downstream tools it feeds.

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 clear when-to-use context: 'look up an app the user names before calling rivioo_review_stats, rivioo_search_reviews or rivioo_get_reviews.' The clause 'Free; delivers no reviews' acts as a when-not for review retrieval. It never explicitly contrasts with rivioo_find_app, which is the closest alternative, 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 cover read-only/idempotent/no-destructive, and the description layers on real behavioral context: it is free, returns no review text, counts only reviews Rivioo holds in the window (not all reviews ever), and auto-collects newer reviews when held data is older than max_age_hours. The store-specific scoping (App Store per country vs Google Play per language across all countries) is information an agent could not infer from the schema alone.

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?

Front-loaded with the core purpose and tightly packed with no filler sentences, but it is a single long run-on paragraph where bullet-style grouping of store semantics and freshness rules would read faster. Every sentence still carries distinct 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?

An output schema exists so return values need no explanation; the description instead supplies the surrounding context an agent needs to call it correctly: window semantics, store-dependent country/language behavior, week boundaries, freshness/auto-collection, and cost. Nothing material is missing for an 8-parameter analytical read 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 adds cross-parameter meaning: how country behaves differently for ios versus android, that App Store results are per country, and that version/week groupings are ordered (newest first, weeks start Monday UTC). It does not restate the days/posted_from/max_age_hours mechanics, which the schema already handles.

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 ('Exact rating distribution for one app over a window') and enumerates exactly what the distribution contains: total reviews, average rating, reviews per star, developer replies, breakdowns by version and by week. The closing 'returns no review text' cleanly separates it from rivioo_get_reviews.

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 explicit use cases ('for ratings, versions and weekly trends, and before reading reviews to see when ratings changed'), which effectively routes the agent toward this tool before get_reviews. It never names an alternative sibling or states a when-not-to-use condition, so it stops short of the top mark.

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 cover read-only/idempotent/open-world safety, but the description adds genuinely non-obvious behavior: the quota model (counts free, each snippet consumes one review of quota the first time it reaches the account in 30 days), pagination via next_cursor with identical arguments, and the per-store scope difference (App Store per country, Google Play per language across all countries). These are real cost and result-shape disclosures beyond the annotations. Slight deduction because it doesn't state whether quota exhaustion errors or silently truncates results.

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?

Purpose and the sibling distinction are front-loaded, and the dense matching/quota/pagination rules each earn their place. It is on the long side with several long run-on sentences (the any_of/all_of and matching rules could be tighter), but 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?

For a 14-parameter, quota-metered search tool with an output schema and full annotation coverage, the description supplies everything an agent needs: what is returned (window reviews, matching reviews, counts per term and per star, snippets with review_id/url), matching semantics, cost, and pagination. The output schema covers return shape, so the description does not need to.

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 enriches the term parameters beyond the schema: literal, case-insensitive word-start matching ("crash" matches crashes/crashed, "ad" does not match "bad"), space-separated terms matching in sequence, CJK matching anywhere, and no translation. It also explains country semantics for both stores. Minor friction: it instructs "Pass next_cursor" while the schema parameter is named "cursor".

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 with scope: "Exact counts of the reviews of one app that mention specific words, plus snippets with review IDs." It explicitly positions itself against the sibling rivioo_get_reviews (counting/sizing vs. reading), so an agent can route correctly without opening either 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?

Names the exact question type it answers ("how many reviews mention X") and the workflow it complements ("sizing themes found while reading reviews with rivioo_get_reviews"), which implicitly excludes the reading use case. The alternative and its selecting condition are stated, not inferred.

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