RocketList

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful context by noting the data is 'public' and includes 'recent active jobs', which gives the agent a sense of access level and content scope beyond the 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?

The description is one compact sentence with no filler. The key scoping detail ('by UUID') and the expected content ('public details and recent active jobs') are included without 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?

For a simple read-only tool with one parameter, an output schema, and safety annotations, the description is complete. It states what is returned, how the company is identified, and the public nature of the data. No critical invocation 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?

Schema coverage is 0%, so the description must compensate. It does by specifying that company_id is a UUID, which is a meaningful semantic addition over the schema's bare 'string' type. With a single required parameter, this is sufficient for correct invocation.

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 ('Get') and resource ('public details and recent active jobs for one hiring company'), and identifies the key identifier as UUID. This clearly distinguishes it from sibling search tools like search_companies and search_jobs.

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 clearly indicates the tool is for fetching a single company by UUID, which implies it is not for searching. It does not explicitly name alternatives or exclusion conditions, but the scope is clear 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 readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds 'public' and 'active' scope but does not disclose additional behavior such as error conditions when the job is not found or inactive. This is adequate but not rich.

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, front-loaded sentence with no filler. Every element—scope, resource, and identifier format—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 single-parameter read operation with an output schema and complete annotations, the description covers everything needed to invoke the tool correctly. No additional return-value or safety documentation is necessary.

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 only says job_id is a required string with no description. The description compensates by explaining that job_id accepts either a slug or a UUID, which is meaningful semantic information 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?

The description states a specific verb ('Get'), a precise resource ('one active Rocketlist job'), and the exact lookup keys ('by slug or UUID'). It clearly distinguishes this tool from the search-oriented siblings like search_jobs.

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 makes the use case clear: retrieve a single known active job by slug or UUID. It does not explicitly name alternatives or exclusions, but the contrast with search_jobs is strongly implied by 'one active ... by slug or UUID.'

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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: it states the return is bounded and non-personal, that only companies with active jobs are returned, and that certain filters exclude companies with missing investor/stage data. It also warns that passing a bare string to list arguments is a validation error. This is strong additional behavioral disclosure, though it doesn't detail pagination or exact result shape, which the output schema likely covers.

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 well-structured with a clear opening sentence, a scope note, a type warning, and labeled filter sections. It is longer than minimal but every sentence adds meaningful information about behavior or parameter semantics. The only minor inefficiency is the slight redundancy between the opening scope statement and the 'Only companies with at least one active job' sentence, but this is acceptable for emphasis.

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 tool's moderate complexity (4 optional parameters, no required params, output schema present), the description is complete. It covers what the tool returns, the filtering semantics, data-coverage caveats, and type requirements. The output schema handles return-value details, and annotations handle safety. An agent has everything needed to select and invoke this 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 0%, so the description carries the full burden of explaining parameters. It thoroughly explains query (substring of name/slug or whole sector word), investor (aliases resolve, ~83% population), and stage (exact enum list, case-insensitive, ~12% missing). It also clarifies the list-argument type requirement. The limit parameter is not explicitly described, but its name and default in the schema are self-explanatory, and the description's depth on the other three parameters more than compensates.

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 and resource: 'Search public Rocketlist hiring companies.' It immediately distinguishes itself from siblings by stating it returns bounded, non-personal company data and only companies with active jobs, which clearly separates it from get_company, get_job, and search_jobs.

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 states when to use this tool: to search public hiring companies, and it clarifies that only companies with at least one active job are returned, matching the company list on rocketlist.ai. It also provides detailed filter semantics and notes that certain filters exclude companies with missing data, giving clear guidance on when results may be incomplete. While it doesn't explicitly name sibling alternatives, the scope and filter behavior make usage conditions 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?

Beyond the annotations (readOnlyHint, idempotentHint), the description discloses many behavioral traits: prefix token matching, substring semantics, exact-match behavior for domain/stage, investor alias resolution, and concrete exclusion behavior when data is missing (83%, 12%, 56% coverage). It also states the array-type validation rule. This significantly exceeds what annotations alone 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?

The description is front-loaded with the core purpose, then organized as a clear bulleted filter list. Every sentence adds operational value: matching behavior, coverage percentages, and example values. Despite length, there is no filler or redundancy, and the structure makes scanning easy.

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 10-parameter search tool with an output schema, the description covers almost everything an agent needs: filter semantics, missing-data side effects, and input validation. The only gap is the limit parameter (pagination/result cap), which is not described; 'bounded' hints at it but does not explain how limit controls it. Otherwise, the caveats and examples make the tool safely callable.

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 0%, so the description carries the full burden, and it delivers. Every filter parameter except limit gets a detailed semantic explanation including matching rules, examples, and caveats. The global note that list arguments must be arrays of strings clarifies validation. The only omission, limit, is a self-explanatory integer with a default in 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?

The description opens with a specific verb and resource, 'Search public active Rocketlist jobs', immediately stating the operation and scope. It clearly differentiates from siblings by focusing on searching jobs rather than retrieving single entities (get_company, get_job) or searching companies (search_companies). No tautology or ambiguity.

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 extensive context on how filters work and what limitations apply, such as non-personal data and partial coverage for investor/stage/experience. However, it never explicitly tells the agent when to prefer search_jobs over get_job or search_companies, nor when not to use it. The routing to alternatives is only implied by the presence of sibling tool names.

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