Shipstry Launch Data

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

Annotations already establish a safe read (readOnlyHint, idempotentHint, destructiveHint=false), and the description adds real context beyond them: the normalization parity with submission duplicate detection and the critical caveat that only approved listings are visible, so pending submissions won't be found. It stops short of describing the response shape or any rate limits.

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 tight sentences with no filler; the core behavior comes first and the visibility caveat second, which is the right front-loading for a boolean-style check.

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 annotations covering the safety profile and no output schema, the description covers the essentials, including the important limitation on which listings are visible. Only the nature of the returned result is left unstated.

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 a single url parameter and 0% schema description coverage, the schema alone gives no meaning. The description partially compensates by tying the parameter's interpretation to the submission-normalization rules, but adds no format, protocol, or length guidance.

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 (check) and resource (URL listing status on Shipstry), and clarifies the normalization basis, which distinguishes it from search_launches-style tools. It doesn't explicitly name a sibling, but none of the siblings overlap in function.

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 'same normalization as submission duplicate detection' implies the pre-submission duplicate-check use case, but it never states when to prefer this tool over search_launches or what to do with a true/false result. Usage is implied rather than instructed.

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 safety (readOnlyHint, idempotentHint, openWorldHint=false, destructiveHint=false), so the bar is low. The description adds real behavioral context by disclosing what the result contains (launch counts, vote percentiles, top launches, medal counts, top tags), which is more than the annotations convey, though it says nothing about cost, rate limits, or pagination.

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 scope are front-loaded in the first clause, and the second sentence handles usage. The middle enumeration of output metrics is dense but each item earns its place by telling the agent what it will receive; only minor tightening is possible.

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?

There is no output schema, so the description must carry return-value disclosure — and it does, listing the aggregate metrics, top launches, medal counts, and tags. Combined with annotations covering safety and a 100%-documented schema, an agent has everything needed 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 description coverage is 100%, with both the weeks window (default 12, range 1-52) and the category enum fully documented in the schema. The description's phrase 'window of ship weeks' merely restates that, adding no format or syntactic detail beyond the structured fields, 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 states a specific verb and resource ('Benchmark a category') plus the scope ('over a window of ship weeks') and enumerates the aggregate outputs, making it clearly distinct from launch-level siblings like get_launch or search_launches.

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 gives a concrete decision context: 'Use this to judge how crowded a space is and what a winning launch looks like there.' That is clear when-to-use guidance, but it names no alternative tool or exclusion condition to route the agent against siblings like get_winners or search_launches.

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 safety is covered. The description still adds real value by disclosing the 'approved' filter and the returned field set, which matters since there is no output schema. It stops short of failure behavior for unknown identifiers.

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 tight sentences, counter and identifier list front-loaded, no filler or restatement of the title.

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 three-parameter read tool with no output schema, naming the returned fields and the accepted identifier forms covers most of what an agent needs. The remaining gap is edge behavior: not-found handling and the fact that supplying no identifier is invalid.

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 67% with the slug parameter undocumented, and the description fills that gap by naming it 'product slug' and clarifying that the url parameter accepts either a Shipstry product URL or the product's own website URL. It does not state that all three identifiers are optional or what happens when none is supplied.

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 ('Fetch') and resource ('one approved launch'), and enumerates exactly what comes back (description, tags, awards, maker name). The singular scope cleanly separates it from the plural discovery sibling search_launches.

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 tells the agent how to target a launch (four identifier forms) but never states when to reach for this tool versus search_launches, get_winners, or check_url. Usage is implied by 'one approved launch' rather than stated.

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 this a safe, idempotent, read-only operation, lowering the bar. The description adds genuine behavioral context beyond them: default returns the most recent periods, while supplying `period` narrows to a single period. Return/pagination mechanics are not described, but that gap is minor given the annotation coverage.

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 what the tool returns and zero redundancy. Each sentence earns its place: contents, default-vs-explicit period behavior, and usage context.

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 annotated read tool with no output schema, the definition covers purpose, default scoping, and usage context adequately. It omits how `limit` caps or paginates results, a small but real gap for an agent deciding how to call it.

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 67% – scope and period carry their own descriptions, but `limit` (default 12, max 60) is undocumented in the schema and is never mentioned in the description either. The description's note about 'most recent periods by default' adds marginal meaning to `period`, so it neither compensates for the gap nor falls below the 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?

States a specific verb+resource and precisely what is returned: weekly/monthly medal winners ranked gold/silver/bronze. The clause 'see what actually won, not just what launched' distinguishes it from the launch-oriented siblings (search_launches, list_ship_week) 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?

The 'use this to see what actually won, not just what launched' line gives clear context for when this tool is the right choice versus launch-listing tools. It stops short of naming an explicit alternative tool or stating when-not to use it, so it lands just below the top band.

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?

The annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so safety is covered. The description adds useful behavior beyond that: it is a complete read-only listing (no params, no filtering) and describes the returned payload (categories with approved-product counts).

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 tight sentences with zero waste. The purpose is front-loaded and the when-to-use hint follows immediately.

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 zero-parameter listing tool whose annotations carry the safety profile, the description covers what it returns and why to call it. Minor gaps remain around result ordering or pagination, but those are low-risk for a taxonomy list.

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 parameterless, unfiltered listing, and there is nothing further it could add about 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?

States a specific verb and resource ('List Shipstry's product categories') and adds the payload detail ('number of approved products in each'). It is clear, but it never differentiates itself from the closely related sibling get_category_landscape, leaving the agent to infer the boundary.

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 an explicit call condition: 'Call this first when you need a valid category slug for the other tools.' This is clear workflow context, though it refers to 'the other tools' generically rather than naming get_category_landscape or another alternative to disambiguate against.

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 establish this as a safe, idempotent read, so the bar is lower; the description still adds real behavioral context by disclosing that Fog Mode hides the current week's vote counts and randomizes ordering. It stops short of describing pagination or response shape, but that is largely carried by limit/offset in the schema.

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 tight sentences with no filler, and the core behavior (what is listed) is front-loaded ahead of the conditional Fog Mode caveat. The parenthetical week formatting is dense but 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?

For a 5-parameter, read-only list tool with no output schema, the description covers the non-obvious behaviors an agent needs (week defaulting, Fog Mode vote hiding and random ordering). It could say more about the return shape or pagination expectations, but nothing critical 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?

Schema coverage is 60%, so the description needs to add meaning, and it does: it clarifies shipWeek is keyed to the Monday in YYYYMMDD form with a current-week default, and explains that sort's 'votes' mode is forced to random under Fog Mode. limit/offset and category receive no extra prose, but they are self-evident given ranges and the enum.

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 gives a specific verb and resource ('List the products that launched in one ship week') and even defines the week's semantics (Monday-Sunday UTC, YYYYMMDD key). It is clear what the tool returns, though it never names or contrasts itself with siblings like search_launches or get_winners, so the agent must infer the boundary.

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 states the default (current ship week) and a conditional behavior under Fog Mode, which implies when the tool is useful, but it offers no explicit when-to-use / when-not-to-use guidance or pointer to an alternative such as search_launches for cross-week queries. Usage is implied rather than instructed.

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 and non-destructive, so safety is covered. The description adds genuinely useful behavioral context: results are limited to 'approved' launches only, keyword scope is product name and tagline, and the return payload is compact (votes, ship week, awards, canonical URL).

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: filters, keyword scope, and return shape. Information is front-loaded with the operation and scope before the payload detail.

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 correctly compensates by naming the returned fields, and the 'approved' constraint plus filter facets are enough to call the tool correctly. The only shortfall is the absence of any guidance on sorting, pagination, or result volume for a 6-parameter search 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 67%, so the baseline is 3. The description restates the keyword scope already documented on 'query' and names category/tag usage, but says nothing about sort, limit, or offset, which is where the schema is thinnest (limit and offset carry no prose description). It adds marginal value rather than compensating for the gap.

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+scope ('Search approved Shipstry launches by keyword, category, or tag'), which cleanly separates it from siblings such as get_launch (single item), list_ship_week, and get_winners. An agent can route to it without opening the 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?

Usage is implied by the faceting description (keyword/category/tag), so an agent can infer when the tool applies. However there is no explicit when-to-use versus when-not, and no pointer to alternatives like get_launch for fetching a known launch or get_category_landscape for discovering tags.

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