guichet

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

Annotations declare readOnlyHint=false, idempotentHint=false, and destructiveHint=false. The description adds crucial context: it creates a live payment session, returns a URL, but charges nobody by itself, and warns against completing the payment. This goes beyond the annotations by clarifying the tool's side effects (session creation without charging) and the expected agent behavior (hand off the 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?

The description is three sentences, front-loaded with the core action and purpose, then adding necessary details (price, timeline, refund, and the 'never complete payment' instruction). Every sentence earns its place; there is no fluff or repetition of schema content.

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 output schema exists (so return format is documented elsewhere), the description fully covers what the tool does, when to use it, what to do with the result, and a critical precondition. An agent can safely invoke it without additional clarification.

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. The description adds the age constraint ('less than 30 days old') on submission_id, which is not in the schema, and clarifies that submission_id comes from submit_pwa. Email is adequately covered by the schema, and the description adds no redundant detail. The added constraint raises the score.

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 opens with a specific verb+resource ('Create a Stripe Checkout link') and a precise purpose ('upgrade an existing submission to Pro Launch'), which immediately distinguishes it from all siblings (none of which create payment links). It also specifies price, timeline, and refund policy, leaving no ambiguity about what the tool accomplishes.

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 direction: it requires a submission_id from submit_pwa that is less than 30 days old, and it instructs the agent to give the URL to the user and never attempt to complete the payment. This is clear, actionable guidance that also implies when not to use it (e.g., for new submissions or when the ID is stale).

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?

Beyond the readOnlyHint, the description discloses important behavior: it 'Returns found:false rather than an error when the slug is not in the catalog', which prevents the agent from misinterpreting missing results. It also adds a safety instruction about third-party listing content, which is valuable operational context not present in 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?

Four concise sentences with no filler. The primary purpose is front-loaded, followed by read-only status, not-found behavior, and a safety caution. Every sentence adds value.

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 a single well-documented parameter, strong annotations, and an output schema present, the description covers the core behavioral expectations: read-only operation, not-found semantics, and content handling. Nothing essential is missing for an agent to invoke 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?

The schema already fully documents the slug parameter with pattern, length, and description. The description reinforces that the slug comes from search_pwas, matching the schema, but adds no new semantic detail beyond that. With 100% schema coverage, a baseline of 3 is appropriate.

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 uses a specific verb and resource: 'Fetch one catalog listing in full by its slug'. It clearly distinguishes itself from search_pwas by indicating it retrieves one listing by slug, and names the source of the slug. This makes the tool's role unambiguous among 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 says the slug is 'as returned by search_pwas', which implicitly tells the agent to use this tool after searching and when a specific slug is known. It lacks an explicit 'use this instead of X' statement, but the context is clear enough for correct tool selection.

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 and non-destructive behavior; the description adds valuable context: cost (€49), review timeframes (4 weeks vs 48h), and reiterates 'read-only, and cheap.' This goes beyond the annotations without contradiction.

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, each earning its place: core purpose, pricing/timing, and a usage tip. Front-loaded and free of 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 an output schema exists (so return values are documented elsewhere), the description covers all relevant context: what info is returned (fields, categories, tiers), pricing, timing, and when to call it. Complete for a zero-parameter 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?

There are zero parameters, so schema coverage is trivially 100%. The description does not need to explain parameters; instead it focuses on the output content, which is appropriate. Baseline 4 applies due to 0-param nature.

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 exactly what the tool does: lists required/optional fields, rules, catalog categories, and review tiers for submit_pwa. It explicitly differentiates from sibling tools by naming submit_pwa and framing the tool as a prerequisite, making its purpose unmistakable.

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 clear when-to-use guidance ('Call it before submit_pwa rather than guessing a category') and contextual pricing/timing info. It does not mention alternative tools or exclusions, but the directive is strong and unambiguous.

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 indicate read-only and idempotent behavior, but the description adds valuable disclosure: it never returns personal data, the handle is a lookup key rather than a credential, and stale handles over 30 days are rejected. It also states exactly which data is returned, going well beyond the annotation hints.

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 compact and front-loaded with the purpose, with each sentence carrying useful information. The only minor redundancy is 'Read-only,' which duplicates the readOnlyHint annotation, but it is not bloated enough to lower the score further.

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 single-parameter, read-only status tool, this description covers what it returns, where the ID comes from, important temporal constraints, and privacy guarantees. The presence of an output schema further reduces the burden, and nothing an agent needs to call it correctly 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 100% and already explains the submission_id format and its non-credential nature. The description adds meaning on top by specifying the ID comes from submit_pwa and that handles older than 30 days are rejected, so it is more than a baseline 3.

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 starts with a specific verb+resource: 'Report where one submission stands.' It then enumerates the returned fields (app name, URL, submission date, tier, published status), which clearly distinguishes it from listing/searching tools like search_pwas and get_pwa. The explicit link to submit_pwa's returned ID anchors its role in the workflow.

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 gives clear context: call it with the submission_id returned by submit_pwa, and note that handles older than 30 days are rejected. It doesn't explicitly state when not to use it or name alternative tools for different needs, so it stops short of a 5.

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 description adds useful behavioral context beyond annotations: results are capped at 20 regardless of requested limit, and listing text is third-party content that should be reported rather than followed. The read-only and idempotent traits are already in annotations, so the description does not need to repeat them, but the cap and content warning are valuable additions.

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, all informative and free of filler. The core action and return value are front-loaded, followed by important behavioral caveats. Every sentence 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?

The description covers the purpose, output shape, API cap, and safety guidance, while the schema fully documents all parameters. With an output schema present and no nested objects or complex invocation requirements, nothing essential 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 description coverage is 100% and each parameter already has a meaningful description. The tool description does not add extra parameter-level meaning beyond what the schema provides, which meets the baseline for high schema coverage.

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 (search), a clear resource (the pwa.directory catalog), and what the tool returns (listing summaries with slug, name, description, category, tags, and URL). This clearly distinguishes it from siblings like get_pwa, which presumably fetches a single app rather than performing a catalog search.

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 gives clear context: use this to search the PWA catalog and get listing summaries. It does not explicitly name alternatives or state when not to use the tool, but the search-and-summaries framing makes the appropriate use case evident.

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 provide readOnlyHint=false, idempotentHint=true, and destructiveHint=false; the description adds valuable specifics: writes to the moderation queue, emails a receipt, human review before publication, 30-day handle expiry, and 'holding the handle authenticates nobody.' 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?

Every sentence earns its place: primary action and side effects first, then timeline, idempotency, handle lifetime, authentication non-effect, and eligibility. Dense but not bloated, and the most decision-relevant facts are front-loaded.

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 8-parameter write operation, the description covers process, human-review expectations, idempotency behavior, handle expiry, and authentication semantics. The output schema handles return shape, so 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 100%, so the schema carries most parameter meaning. The description still adds behavioral context beyond the schema by tying contact_email to a receipt email and spelling out the idempotency_key replay semantics as an application-level mechanism rather than a protocol feature.

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 states a specific verb and resource: 'Submit one progressive web app for review.' It distinguishes itself from read/search siblings by describing the moderation queue, receipt email, and human review pipeline, and references related tools only for handle-lifetime behavior.

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 context for use: human-reviewed queue, four-week timeline, and 'Submit apps that exist and that you can name' as an eligibility guideline. It does not explicitly state when not to use the tool or name an alternative like get_submission_requirements, so it stops short of full alternative routing.

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