Website Feedback Tool

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

No annotations are provided, so the description carries the full behavioral burden. It usefully enumerates the payload contents (comments, selectors, computed styles, console/network errors, screenshot URLs) and the Markdown format, but says nothing about read-only status, auth requirements, or what happens when no review exists.

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?

One sentence, front-loaded with the resource and scope, with the parenthetical payload list earning its place by telling the agent what it will receive. 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?

With no output schema, the description compensates by enumerating the returned content, which is the key thing an agent needs. It is slightly short on failure/empty-state behavior, but adequate for a zero-parameter read.

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 and the description correctly introduces none, so baseline 4 applies. There is no parameter semantics to add or omit.

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 (Get) and resource (design review) with a clear scope qualifier, 'most recent', which implicitly separates it from get_review and list_reviews. It stops short of naming the sibling it is not, so differentiation must be inferred.

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 only implied by the 'most recent' scope; the description never states when to prefer this over get_review or list_reviews, nor any precondition such as a review having been created. An agent can guess the intent but gets no explicit routing help.

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?

No annotations are provided, so the description carries the full behavioral burden. It discloses the response format (Markdown feedback) and 'Get' implies a safe read, but it says nothing about what happens on an unknown id, permission requirements, or size/length of the returned review.

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 short sentences with zero filler; the core action and output format come first and the dependency hint follows.

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, and the description compensates by naming the return format (Markdown feedback). For a single-parameter read tool this is nearly complete, missing only failure behavior and any access constraints.

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 the schema already gives the id format example (rvw_abc123…). The description only adds where to obtain the id, which is baseline-level value 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?

States a specific verb+resource ('Get one design review by id') and adds the return format ('as Markdown feedback'). The 'by id' qualifier implicitly separates it from get_latest_review, though that sibling is never named explicitly.

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 a concrete precondition by directing the agent to list_reviews for the required id, which is genuine routing guidance. It stops short of stating when not to use this tool (e.g. to get the newest review, use get_latest_review).

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?

No annotations are provided, so the description carries the disclosure burden. It usefully reveals that the image is returned inline rather than as a fetchable URL, which is the key behavioral trait of the tool, but says nothing about permissions, error behavior, or how authorization differs for the share-link path (that detail lives only in the schema for '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?

Two tight sentences, front-loaded with what the tool does and followed by the routing instruction. Every clause earns its place, including the parenthetical explaining why the tool exists.

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, and the description compensates by stating that the screenshot is delivered inline. It omits any note about authorization differences between the reviewId path and the share-link path, but for a simple two-required-parameter read tool it is nearly 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%, so reviewId, commentId, and the conditional 'url' parameter are already fully documented in the schema. The description repeats the commentId provenance ('shown next to the screenshot in get_review') without adding syntax or format meaning beyond it, 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 ('View a comment's screenshot inline') and immediately distinguishes itself from generic URL fetching by noting clients don't fetch image URLs themselves. It also names get_review as the source of the required id, so an agent can tell it apart from siblings without reading any 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?

Gives clear context: use it when you need to see a comment's screenshot, and it tells the agent exactly where to obtain the reviewId and commentId (get_review). It does not state any when-not conditions or name a competing alternative, but the routing to get_review is explicit.

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?

With no annotations, the description carries the full burden and does well: it discloses ordering (newest first), provenance (browser extension), and the returned field set. It stops short of stating how many reviews are returned, any window/limit on 'recent', or explicitly confirming the call is a read-only, side-effect-free operation.

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 compact sentences: the payload description first, then the action guidance. No filler, no redundancy, and the field enumeration doubles as the output documentation.

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 and no annotations, so the description must stand in for both — and it enumerates the returned fields and the downstream reviewId, which covers the essentials. The remaining gap is result cardinality and any extension-availability prerequisite.

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, which is the baseline-4 case; there are no arguments whose meaning could be ambiguous. The description instead clarifies the output shape, which is a sensible use of space.

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 your recent design reviews') and goes further to name the data source (Design Review browser extension), the sort order (newest first), and the exact returned fields. An agent can distinguish this from get_review and get_latest_review without opening a 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?

'Use this to pick which review to apply' gives a clear intent and explicitly routes the agent to get_review via the reviewId, which is a strong downstream link. It does not, however, contrast with the sibling get_latest_review for the single-most-recent case, leaving that selection 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?

With no annotations, the description must carry the behavioral burden, and it does disclose key traits: the link carries its own access (no local push/auth needed), it is not persisted into list_reviews, and the output is Markdown. It does not cover failure modes such as expired or malformed links, which is the remaining 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?

Three sentences, each carrying distinct information: what it does, when to use it, and its persistence behavior. Front-loaded with the action and output format, with 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 a single-parameter tool with no annotations and no output schema, the description covers purpose, routing, access model, and return format, which is nearly everything an agent needs. It stops short of describing behavior on invalid or expired links.

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?

Only one parameter and schema description coverage is 100%, so the schema already documents the url field and its ?t=… requirement. The description's mention of the '/r/<id>?t=…' URL shape restates rather than extends 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?

States a specific verb and resource ('open a design review from a share link') plus the return shape ('get its feedback as Markdown'). It also differentiates itself from list_reviews by noting the link stays out of the list, so an agent can choose between them without inspecting schemas.

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 states the trigger condition ('when the user pastes a review link rather than asking for their own reviews') and contrasts it with the sibling list_reviews. The note that the review need not have been pushed from this machine further clarifies when it applies.

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