Cassette Game Finder

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so the safety profile is covered. The description contributes behavioral context the annotations cannot: the exhaustive breadth of returned data ('everything Cassette knows'), which matters because there is no output schema. It omits what happens when the slug is unknown or the game has no demo/price, a minor 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?

Two sentences, zero filler. The content enumeration comes first and the usage trigger second, so the agent reads the scope before the routing hint. Every clause carries 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 one-parameter read tool with strong annotations and no output schema, the description covers both what is returned and when to reach for it, which is what an agent needs to act. The only missing piece is error behavior for an invalid or unmatched slug, which is a small omission given the tool's simplicity.

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 schema already explains that 'game' is the slug returned by search_games, including the cross-reference to the sibling. The description adds no format, casing, or fallback guidance for the identifier, so it does not exceed the baseline set by a fully documented single 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?

The description names the resource precisely ('one game') and enumerates what comes back: description, facts, price, demo, maker, screenshots, store page and play link. That is far more informative than the title 'Get one game'. It lacks an explicit retrieval verb, but the scope is unambiguous enough that an agent can distinguish it from list-style 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?

'Use it before you recommend a game you only know from a list' gives an explicit trigger condition and implicitly routes the agent away from acting on thin list data alone. It does not name the alternatives (search_games, similar_games) or state when-not to use it, so it falls short of full when/when-not/alternatives 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 declare readOnly, idempotent, closed-world, non-destructive, so the safety profile is covered. The description adds that results include counts and community genres, but doesn't describe ordering, size, or caching behavior of this no-param listing.

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 sentences, front-loaded with what is returned and followed by usage purpose. Slightly dense phrasing in the first sentence but no wasted words.

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 no-param, read-only enumeration without an output schema, the description covers content and purpose adequately; a small gap is left about result size or shape, but nothing needed to invoke it is missing.

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?

Zero parameters, so the baseline is 4; the description correctly implies a single unfiltered aggregate call with nothing to configure, leaving no parameter ambiguity for the agent.

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 (genres and most-used tags) and adds concrete detail: counts per genre/tag and community-game genres. That's more than a name restatement, though it doesn't differentiate itself from siblings like search_games directly in purpose terms.

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 gives two when-to-use conditions: choosing vocabulary for search_games, and checking what Cassette offers before making promises. It names the sibling tool to use next and the intent that selects this 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, so the safety profile is covered. The description adds genuinely new behavior: hosted games ranked before community games, the per-game fact bundle returned, and the important rule that community results are dropped when filtering by multiplayer, age or size. No contradiction with 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?

Three sentences, front-loaded with the action, then return contents, then ranking and the empty-result rule. The parenthetical fact list is long but each item is decision-relevant; nothing is 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 12 optional parameters and no output schema, the description does the necessary work of sketching the return shape (facts, store page, link) and the ranking order. It leaves pagination/limit and how query matching weighs fields to the schema, which is acceptable but not fully complete.

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%, including enums, defaults and ranges, so the schema already carries parameter meaning. The description adds only the ordering implication of results and the empty-result case, not syntax or filter interaction beyond what the schema states, so 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?

States a specific verb and resource ('find games on Cassette') and what the results contain, so the agent knows exactly what it retrieves. It does not distinguish itself from the sibling similar_games, which could overlap for a vague query, so it falls short of a 5.

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 operating guidance: use a plain-language query or omit it to list most-played games, and treat an empty result as a real answer to relay to the user. It never names an alternative tool (e.g. similar_games) or says when this is the wrong choice, so exclusions are missing.

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 safety profile (readOnly, idempotent, non-destructive), so the description's job is to add behavior — and it does: it discloses the weighting scheme behind the ranking and guarantees determinism ('the same game always gets the same answer'). It doesn't state how many results come back by default or what happens when a game has no similar matches, but the added context is genuinely useful.

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 earning its place: what it returns, how it scores, and how it is deterministic, followed by the filter hint. The core purpose is front-loaded 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?

For an eight-parameter read tool with a fully documented schema and no output schema, the description covers purpose, ranking logic, determinism, and filter reuse — enough to call it correctly. The one gap is that with no output schema, it never hints at the shape of the result list (fields per similar game, whether a similarity score is included).

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%, so every one of the eight parameters is already self-documenting, which sets the baseline at 3. The description's only parameter-level contribution is the cross-reference that the filters mirror search_games, which is helpful but adds no meaning the schema lacks.

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 — games similar to a given game — and even discloses the ranking mechanism (genres weighted three, tags one). That mechanism plus the 'like a given game' framing cleanly separates it from search_games and get_game.

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 phrase 'Takes the same filters as search_games' tells the agent this is the discovery path once a seed game is known and that the filter vocabulary is shared, which is real routing guidance. It stops short of explicit when-not guidance (e.g. use search_games when you have no seed game), so it is clear context without full exclusions.

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