GMaps Lead Finder

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

With no annotations, the description carries the burden of behavioral disclosure)Skip and it does add meaningful behavior: sharing a single in-flight job limit with the web app and returning 409 if another job is running. It does not mention the success response shape or asynchronous behavior, but the stated concurrency failure mode is valuable.

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 with no filler: the first states the operation and constraint, the second gives the critical concurrency error. Every word earns its place and the key information is 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 a one-parameter create tool, the description covers the essential input and a key error condition. However, because there is no output schema, it does not explain what a successful call returns or how to obtain the job's results, leaving that to inference from sibling tools.

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 already documents the keyword parameter with an example. The description's 'exactly one keyword' reinforces the schema but does not add new meaning beyond it.

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 that this creates a Maps search job for a single keyword, using a specific verb and resource. It distinguishes from sibling photo/review job creators by saying 'search job,' though it does not explicitly name the alternative tools.

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 implies usage for one-keyword Maps searches via 'exactly one keyword,' and the 409 conflict note warns against concurrent calls. However, it does not explicitly say when to prefer this over gmaps_create_photos_job or gmaps_create_reviews_job, so routing relies on inference from sibling names.

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 exist, so the description carries the transparency burden. It discloses the nontrivial fact that only one in-flight job is allowed and that the API returns 409 when busy, plus the accepted single-place forms. It stops short of stating whether the job is asynchronous and what the immediate response contains, but the core behavioral constraints are clear.

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, purpose first, with no filler. The format list is compact and the concurrency note 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 one-parameter create-job tool this is largely complete: place formats, single-place restriction, and job-limit behavior are covered. It does not describe the return payload or how to fetch results, but the sibling get_photos_job/get_photos_results tools imply the workflow.

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 covers the single place parameter at 100%, so the description adds little beyond restating accepted formats; it does reinforce 'exactly one place,' which is marginally useful. Baseline 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?

Description uses a specific verb ('Create'), names the resource ('Google Maps photos scrape job'), and narrows scope to exactly one place, listing accepted identifier formats. This cleanly separates it from gmaps_create_reviews_job and generic gmaps_create_job.

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 clearly indicates this is the photos-job variant and adds a concurrency condition (single in-flight job limit, 409 if busy), so an agent knows when it may fail. It does not explicitly name sibling alternatives such as gmaps_create_reviews_job, but the photos scope is 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?

With no annotations provided, the description carries the full burden. It discloses a critical behavioral trait: the single in-flight job limit shared with maps jobs and the 409 error when busy. It also clarifies the input acceptance format (URLs, short links, business_id). It does not mention return value or authentication, but the concurrency behavior is a significant operational 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?

The description is two sentences with zero waste. The purpose is front-loaded, followed by accepted input formats and a key concurrency caveat. Every clause contributes.

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 and a key constraint, but it does not explain what the job returns or how to retrieve results, which is especially important given there is no output schema. The agent would benefit from a note about using gmaps_get_reviews_results after creation, but the sibling tools and the word 'job' imply that follow-up.

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 input schema already describes the 'place' parameter exhaustively, detailing accepted formats (Maps URL, short links, business_id). The description reiterates the same formats without adding new meaning. The 'exactly one place' constraint is a behavioral note, not parameter semantics, so the schema does the heavy lifting; baseline 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 clearly states the tool creates a Google Maps reviews scrape job and specifies it is for exactly one place. This distinguishes it from sibling create tools like gmaps_create_photos_job, which target photos, and gmaps_create_job, which is generic.

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 that this is for reviews and that it shares a single in-flight job limit with other maps jobs, warning of a 409 error when busy. However, it does not explicitly state when to use this tool over alternatives such as gmaps_create_photos_job, relying on the name and implicit purpose.

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 behavioral disclosure burden. It discloses that the tool returns status plus per-keyword file metadata and that it supports polling until terminal states. This is meaningful behavioral context beyond a bare 'get job status', though it does not detail error behavior or read-only guarantees.

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 short sentences with no filler. The first sentence states what the tool does, and the second adds the essential polling instruction. Every word 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 one-parameter polling tool with no output schema and no annotations, the description is largely complete: it names the operation, the return focus, and the expected polling pattern. It could more clearly define what 'per-keyword file metadata' means or describe the final response structure, but that is not critical for invoking the tool 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 the jobId parameter already documented as 'Job UUID from gmaps_create_job'. The description adds no additional parameter-level meaning, so it lands at the baseline for a fully covered 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?

The description states a specific action ('Get') and resource ('maps job status and per-keyword file metadata'), making the core purpose clear. It does not explicitly contrast with sibling tools like gmaps_get_photos_job or gmaps_get_reviews_job, but the generic 'maps job' phrasing is enough to imply it is the non-specialized status endpoint.

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 instruction to 'Poll until status is completed, partial, or failed' gives a clear, actionable usage context: this tool is meant to be called repeatedly until a terminal job status appears. It does not name alternatives or exclusions, but for a polling endpoint this is sufficient 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?

With no annotations, the description carries the burden. It discloses the asynchronous polling nature and terminal states, which is valuable. However, it does not mention non-terminal status values, error behavior, or any result payload details.

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 the main action first and no filler. Every word adds value, especially the explicit polling instruction.

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 status-check tool, the description covers the core necessity: what to poll and when to stop. It omits a pointer to the next step (e.g., gmaps_get_photos_results) and non-terminal statuses, but these are not required to invoke the tool 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 fully describes the single parameter jobId as 'Job UUID from gmaps_create_photos_job' (100% coverage). The description adds no parameter-specific information, 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 ('Get'), resource ('photos job status'), and terminal states ('completed, partial, or failed'). The 'photos' scope distinguishes it from generic siblings like gmaps_get_job and from result-fetching tools like gmaps_get_photos_results.

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: poll until a terminal status is reached. This implies when to use the tool (after creating a job, repeatedly until completion). It does not explicitly name alternatives or exclusions, but the guidance is sufficient.

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 behavioral disclosure burden. It adds useful traits: results are paginated, returned as JSON, and only for finished jobs. However, it does not disclose what happens for an unfinished job, the structure of the result rows, or the pagination contract beyond what the schema already states.

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 a single sentence that states the core behavior, result format, and precondition without waste. It earns its place by being immediately scannable and informative.

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 and schema together let an agent identify the tool, its precondition, and its parameters, but no output schema exists and the description does not explain the result row shape or how this relates to sibling result/job tools. It is adequate but leaves meaningful gaps.

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 jobId, limit, and cursor are already documented. The description adds no extra semantic detail about the parameters, merely mentioning pagination generally. Baseline 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 ('Fetch') and resource ('paginated photo rows as JSON') and conditions it on a finished photos job. It is clear about what the tool returns, though it does not explicitly contrast it with sibling tools like gmaps_get_photos_job or gmaps_get_results.

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 'for a finished photos job' implies the tool should be used after a job has completed, but it does not explicitly state when to use this versus gmaps_get_photos_job, gmaps_get_results, or gmaps_get_reviews_results. No exclusion or alternative guidance is provided.

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 provided, the description carries the disclosure burden. It adds useful behavioral context: the operation is a fetch (read-only), the result is paginated JSON, and output respects user export column preferences. It does not disclose behavior for incomplete jobs, error conditions, or pagination termination, but it offers more than a bare verb.

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?

A single sentence that front-loads the action and resource, then adds the two most decision-relevant constraints: pagination and user column preferences. Every clause 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 simple 3-parameter paginated fetch with no output schema, the description covers the core lifecycle precondition, the output format, and a behavior that affects result shape. It would be marginally stronger if it pointed to gmaps_get_job for checking completion, but the tool is adequately specified for correct invocation.

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 schema already explains jobId, limit, and cursor. The description adds only general context ('paginated', 'respects user export column preferences') rather than parameter-specific semantics, which is acceptable but not additive beyond the schema 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?

The description names a specific verb ('Fetch'), a specific resource ('paginated place rows as JSON'), and a lifecycle condition ('for a finished maps job'). It also distinguishes this tool from siblings like gmaps_get_photos_results and gmaps_get_reviews_results by scoping to 'place rows', and from gmaps_get_job by scoping to results rather than job status.

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 'for a finished maps job' gives a clear precondition and implies this is the results-retrieval step after job completion. However, it does not explicitly state when not to use it, nor does it name alternatives such as gmaps_get_photos_results or gmaps_get_reviews_results for non-place results.

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 provided, the description carries the behavioral disclosure burden. It usefully reveals that this is an asynchronous polling operation and names the terminal statuses, which goes beyond the schema. It does not mention polling intervals, response shape, or error handling, but the core behavior is disclosed.

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 core purpose and immediately followed by the actionable polling instruction. Every word earns its place 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 simple one-parameter status poller, the description is largely complete: it states the purpose, the polling behavior, and the terminal statuses. It could optionally point to gmaps_get_reviews_results for fetching results after completion, but sibling names and workflow context make that 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 description coverage is 100% for the single jobId parameter, including its origin from gmaps_create_reviews_job. The tool description adds no additional parameter meaning, so the 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 clearly states the verb 'Get' and the resource 'reviews job status', distinguishing it from the generic sibling gmaps_get_job and from gmaps_get_reviews_results. The polling instruction reinforces its role as a status-checking tool.

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 usage context by instructing the agent to poll until reaching terminal states: completed, partial, or failed. It does not explicitly name alternatives like gmaps_get_reviews_results for after completion, but the polling guidance makes the intended workflow understandable.

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 itself; it does disclose that this is a paginated, JSON-returning fetch for finished jobs. It does not address error behavior for unfinished jobs, authentication, rate limits, or idempotency, leaving part of the safety profile implicit.

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?

A single, tightly worded sentence front-loads what is fetched, how it is returned, and when it is valid. There is no filler or redundancy.

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?

It provides the essential call-time facts (finished job prerequisite, JSON rows, pagination) and the schema handles parameters, but with no output schema or annotations it leaves row shape and failure behavior undocumented. For a simple paginated fetch this is adequate but not fully self-sufficient.

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 documents all three parameters with 100% coverage, so the baseline is 3 and the description doesn't need to repeat them. The word 'paginated' aligns with limit/cursor but adds no new per-parameter meaning; cursor semantics are already in the schema ('from previous nextCursor').

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 specific action ('Fetch'), resource ('review rows'), output format ('as JSON'), and a lifecycle condition ('finished reviews job'), which clearly separates it from siblings like gmaps_get_reviews_job (job status) and gmaps_get_photos_results (photo rows).

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 operative context: this tool is for retrieving results only after the reviews job has finished, which is the main gate for using it. It doesn't explicitly name alternatives for checking job status or fetching non-review results, so it stops short of full when/when-not 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?

No annotations are provided, so the description carries the behavioral burden. The verb 'Get' implies a read-only operation and 'current' suggests a live query, but it doesn't disclose rate limits, whether the call consumes credits, or error behavior on invalid auth. Adequate but sparse.

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?

A single sentence that front-loads the action and resource with no filler. Every word 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 zero-parameter read tool with no output schema, this description names exactly the key return concepts (plan and credit balance) and the auth scope. An agent has enough information to decide when and how to invoke 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?

There are zero parameters, so the baseline of 4 applies. The input schema is empty and unambiguous, and the description has no parameter details to add.

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 (Get), resource (GMaps Lead Finder plan and credit balance), and scope (authenticated API key). This clearly distinguishes it from sibling tools that handle jobs and results.

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?

No explicit when-to-use or alternative guidance, but the description implies use when checking account plan/credits. Since all siblings are job/result operations, there is no real alternative, but the tool doesn't state this exclusion.

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