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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, openWorldHint), so the bar is lower, and the description adds a genuinely useful behavioral constraint the annotations do not convey: authentication depends on the browser tab being signed in. It does not say what happens when the tab is not signed in (error vs. empty result), which is the one remaining behavioral 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 short sentences, front-loaded with the most useful information (what is returned) and ending with the operational precondition. The first clause is a noun fragment rather than a sentence, and the field enumeration is slightly list-like, but nothing is padded or 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 no output schema, the description carries the burden of describing the return payload, and it does so by enumerating first name, email, user/entity ids, unread message count, and open/closed project counts. Combined with the stated auth prerequisite, an agent has enough to call and interpret the result; only error behavior and response shape details are 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?

The tool takes zero parameters, which is the baseline-4 case; there is nothing for the description to disambiguate. It instead spends its words on return content, which is appropriate for a parameterless call.

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 a concrete resource (the signed-in Angi user) and enumerates exactly which fields it yields, so an agent immediately knows this retrieves the current account profile. It lacks an explicit verb ("retrieves/returns") and never differentiates itself by name from siblings like angi_list_my_projects, but no sibling covers account identity, so the purpose is nonetheless 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?

Usage is implied by the field list plus the prerequisite "Requires the browser tab to be signed in," which tells the agent the calling context. There is no explicit when-to-use statement, no exclusion, and no pointer to an alternative for cases where the tab is not authenticated, so guidance is adequate but thin.

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, openWorldHint, and idempotentHint, so the safety profile is covered. The description adds value beyond them by disclosing the return surface (ratings breakdown, contact address, a review count that is not the reviews themselves) and by flagging that reviews must be retrieved separately — useful behavior for a tool with no output 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?

Two sentences, both earning their place: the first front-loads the resource and its contents, the second handles sibling routing and the review-count caveat. No redundancy or 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-record read with no output schema, the description compensates by enumerating the returned profile sections and noting the separate review-count/review-fetch distinction. Combined with annotations covering safety and a fully 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%, and the schema itself explains profileUrl's expected format, the view enum, and the deprecated compact flag. The description adds no parameter-level detail, so the baseline 3 applies; the schema carries the full burden and does so adequately.

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 (read) and resource (one Angi pro's full profile) and enumerates exactly what the profile contains: business details, service area, hours, amenities, awards, tasks offered, contact address, and ratings breakdown. The final sentence explicitly contrasts it with the sibling angi_get_reviews, so an agent can distinguish it from search/list tools 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?

The description tells the agent what to do when reviews are needed: 'fetch them with angi_get_reviews', routing the complementary task to the correct sibling. It does not state exclusions (e.g., when to prefer angi_search_pros), but the usage context for a single-record lookup is clear.

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, openWorld). Description adds value by disclosing what the records actually contain, including the pro's public response, but omits pagination behavior and whether reviews are capped or ordered.

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: first front-loads the return contents, second gives the filtering affordance. No waste.

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?

No output schema and no annotation gap, but the description does not cover pagination, result ordering, or how the rating filter interacts with limit. For a review-listing tool with a max of 9007199254740991 on limit, ordering/paging context is a real miss.

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 all six parameters including rating bounds and the view enum are documented in the schema. Description mentions rating filtering but adds no format or semantics beyond what the schema already states.

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?

Specific verb+resource with explicit field enumeration (rating, body text, job cost, date, categories, verification flag, response), clearly distinguishing this read-the-reviews tool from angi_search_pros and angi_get_pro 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?

Gives one actionable usage note — filter by rating to isolate complaints or praise — which is also echoed in the schema. But it never states when to use this versus angi_get_pro or angi_list_my_reviews, its nearest siblings.

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 readOnlyHint, openWorldHint, and idempotentHint, but the description adds substantial value: it discloses the exact return fields (bridge role, port, version, extension link states, elapsed time) and the plain-English hint categories that distinguish failure modes. It also states 'Read-only, no auth required,' reinforcing the safety profile with concrete behavioral detail.

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 what the tool does, followed by return details and usage guidance, so the agent hits the important content first. It is dense and slightly long, but every clause carries diagnostic information rather than 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 fully carries the burden of explaining return values and failure-mode interpretation, which it does in detail. An agent has everything needed to call this correctly and interpret the diagnostics.

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 for a 4; there are no arguments whose semantics need explaining. The description correctly signals the parameterless nature by describing an implicit fixed target URL (/robots.txt).

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 (round-trips a small public URL) and resource (ContextMint Bridge connection) and enumerates the diagnostics returned. This is clearly distinguishable from all sibling tools, which fetch account/pro/review/trade data rather than verifying connectivity.

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 says when to use it: 'Call this when a real tool fails and you want to know which hop broke.' This routes the agent correctly relative to the data-fetching siblings. It doesn't name a specific alternative tool or an explicit when-not-to-use, so it falls just 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?

Annotations already declare readOnly, openWorld, and idempotent hints. The description adds useful behavioral context by stating it reads Angi's public sitemap directly and requires no browser bridge, which clarifies prerequisites and execution mode.

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 deliver purpose, usage, and behavioral context with zero filler. The main function is front-loaded, and every clause 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?

For a simple list operation, the description covers the main intent, usage context, and data source. It does not describe the output structure or pagination, but the absence of an output schema and the simple list nature make this a minor gap.

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 the input schema already documents all three parameters. The description adds no significant parameter-level detail beyond what the schema provides, so a baseline score 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 states a precise operation: listing every US state/city Angi publishes pages for, scoped to one trade. This clearly distinguishes it from sibling tools like angi_list_trades or review-related tools by naming the exact resource and filter.

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 explicit use cases: confirm a city slug exists before searching, or discover nearby cities. It does not explicitly name alternatives or say when not to use it, but the intended context is clear.

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/openWorldHint annotations, the description discloses that records are passed through exactly as Angi sends them, that recordFieldsVerified is false, and that field names should be read from data rather than assumed. This is valuable behavioral context that annotations alone do not provide.

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 the core purpose, followed by a necessary caveat about data trustworthiness. No filler or redundant restatement of schema details.

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 one-parameter, read-only list tool, the description covers the resource, scope, and the most important uncertainty (unverified field names). It is slightly less complete because no concrete response shape is hinted at, though the caveat intentionally tells agents not to assume field names.

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 only parameter, status, is already fully documented in the input schema with its enum values and default. The description's mention of open and closed aligns with the parameter but adds little semantic value beyond what the schema provides.

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 clearly states the tool lists the signed-in user's Angi projects, including service requests and bookings, open and closed. This specific verb-resource pairing distinguishes it from sibling tools like angi_list_my_reviews and angi_search_pros.

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 for the signed-in user's own projects, not for general searching or reviews. It does not explicitly name alternatives or exclusions, but the scope is unambiguous enough for correct 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 cover read-only, open-world, and idempotent behavior. The description adds valuable context beyond those hints by disclosing that records pass through raw and that the response sets `recordFieldsVerified: false`, which alerts the agent to unverified data.

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 two concise sentences that lead with the core purpose and follow with the important data-quality caveat. There is no filler or repetition of annotation 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 parameterless, read-only, idempotent tool, the description provides enough detail about what the response contains (`reviews`, `unratedPros`) and a key caveat (`recordFieldsVerified: false`). No output schema exists, but the description supplies the essential return semantics.

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 has zero parameters and the schema coverage is 100%, so there are no parameter semantics to document. The description correctly focuses on the response content rather than inputs, matching the baseline for a parameterless tool.

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 clearly states the tool returns the signed-in user's written reviews plus unrated pros (`unratedPros`). This distinguishes it from sibling review tools like `angi_get_reviews` by anchoring to the signed-in user and their prompted ratings.

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 context for when to use the tool: when retrieving the current user's reviews or rating prompts. It doesn't explicitly name alternatives or state when not to use it, but the scope is specific enough for an agent to select it appropriately.

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, openWorld, and idempotent behavior. The description adds useful context beyond that: it reads Angi's public sitemap directly, requires no browser bridge, and lists approximately 312 entries. This gives the agent an accurate mental model of the 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?

The description is compact and front-loaded: it states the output, gives examples, explains the use case, and notes the data source in three sentences. Every sentence earns its place with no redundant wording.

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 tool with one optional parameter and strong annotations covering safety and idempotency, the description provides everything needed: what it returns, why to call it, how it works, and what it does not require. No output schema is needed since the return type (a list of slug strings) is directly inferable.

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%, with the only parameter 'contains' already documented as a case-insensitive substring filter. The description reinforces the use case but does not add significant new parameter-level meaning beyond what the schema provides, so the baseline 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 clearly states a specific action and resource: 'List every trade slug Angi publishes' with concrete examples. It also names the downstream consumer (angi_search_pros), which distinguishes this tool from sibling tools dealing with reviews, cities, or pros.

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 explicitly says when to call it: 'resolve a free-text trade to the slug angi_search_pros needs.' It does not explicitly mention when not to use it or compare it to alternatives, but the intended usage context is clear enough to guide an agent.

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, openWorld), and the description layers on genuinely non-obvious behavior: the exact fields returned (per-dimension rating breakdown, review count, percent-recommended, years in business, service area, amenities), page size, and the location limitation. That is real added context rather than restatement.

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 sentences, front-loaded with purpose, then return shape, then prerequisites, then the pagination/location caveats. Dense and largely waste-free; the per-dimension rating enumeration is the only passage that runs slightly long against its 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 no output schema, the description takes on the burden of describing returns and does so thoroughly, including the compact/full distinction's effect on payload shape. Prerequisites, pagination, and the missing-filter caveat round out everything an agent needs to invoke 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 does not: `trade`/`city` must be Angi slugs resolved via sibling tools, and location derives only from the city slug. It says nothing about `page` semantics beyond page size or about the `view`/`compact` switch, which the schema carries alone.

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+resource+scope: "Find home-service pros on Angi for a trade in a US city." An agent can immediately separate this from angi_get_pro (single pro) and the list_* helpers, which are named as prerequisites.

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 prerequisite (resolve `trade` and `city` via angi_list_trades / angi_list_cities first) and gives pagination guidance ("10 pros per page; use `page` to walk further"), plus the constraint that no zip-code filter exists. It never spells out when-not to use this versus angi_get_pro, so 4 rather than 5.

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