Corvi Careers

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the action 'List', which implies a read operation, but it does not disclose return format, potential errors, rate limits, or any other behavioral aspects. The description is minimal and leaves much to inference.

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, direct sentence with no unnecessary words. It is front-loaded and immediately conveys the tool's purpose, achieving excellent conciseness.

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 that the tool has no parameters and no annotations, the description is somewhat adequate but lacks detail about the output format or how the returned category slugs might be used in conjunction with sibling tools. It does not specify whether the result is an array, a list of objects, or something else, which would improve completeness.

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, so the baseline score is 4 per the rubric. The description appropriately does not need to explain parameter semantics, and there is no schema to compensate for. The description adds sufficient context by identifying the returned entity (category slugs).

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's function with a specific verb and resource: 'List valid category slugs'. It is not a tautology and it distinguishes itself from sibling tools like location_autocomplete, lookup_companies, and search_jobs by focusing on categories.

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?

There is no guidance about when to use this tool versus the alternatives. It does not mention potential use cases, such as needing a valid category slug before calling search_jobs, nor does it specify any exclusions or prerequisites.

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 alone must disclose behavior. It implies a read-only search but says nothing about case sensitivity, result ordering, or the effect of parameters like min_population and include_country. The tool's operational traits are largely opaque.

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, front-loaded sentence with no redundant words. It is appropriately concise for a simple autocomplete tool, though it could be slightly more specific without becoming verbose.

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 four parameters and no output schema or annotations, the description is too sparse. It does not mention what data is returned, how matching works, or how parameters constrain results. The sibling tools provide some domain context, but the tool description alone is insufficient for reliable 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 0% and the tool description adds no explanation of the four parameters. The agent must guess the meaning of limit, min_population, and include_country from names alone, which is insufficient. The description fails to compensate for the total lack of schema documentation.

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 finds matching locations for job search filters, which differentiates it from siblings like list_categories and lookup_companies by resource type. However, 'matching' is slightly vague and doesn't explicitly say 'autocomplete'.

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 only a weak contextual hint ('for job search filters') and no explicit guidance on when to use this tool versus alternatives. There are no exclusion criteria or mention of sibling tools, leaving usage decisions 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 provided, the description carries the full burden. It only states 'Find matching company names' without disclosing whether the operation is read-only, what it returns, or any potential limitations like rate limits or authorization needs. This is minimal behavioral context.

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, clear sentence with no wasted words. It is front-loaded and to the point, demonstrating excellent conciseness even though it lacks detail.

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 absence of an output schema and annotations, the description is incomplete. It does not explain what the tool returns, how the limit parameter behaves, or the nature of the matching. For a lookup tool, this is insufficient for an agent to invoke it confidently.

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 must compensate. It implies the 'query' parameter is a company name, but it does not explain the 'limit' parameter or the matching semantics (e.g., exact vs partial). The added value is minimal.

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 verb 'Find' and resource 'matching company names', indicating a lookup operation for companies. Although it does not explicitly distinguish from siblings like list_categories or search_jobs, the purpose is distinct enough given the focus on companies.

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 no guidance on when to use this tool versus alternatives. There is no mention of suitable contexts, prerequisites, or exclusions, leaving the agent without clear decision-making information.

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?

There are no annotations, so the description bears the full burden of behavioral disclosure. It only lists searchable fields and says nothing about pagination, default behavior, result ordering, filtering semantics, or any side effects. This is essentially no more than a restatement of the tool's purpose.

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, front-loaded sentence and is not wordy. However, given the tool's complexity (21 parameters, no annotations, no output schema), it is under-specified; conciseness is achieved at the expense of necessary detail.

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 tool lacks annotations and an output schema, and no behavioral or return-value information is provided. With 21 parameters and no clarification on pagination, defaults, or filter interactions, the description is completely inadequate for understanding how to use the tool effectively.

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 has 21 parameters with 0% description coverage, and the description only loosely maps to a subset: keywords, locations, titles, companies, and categories. It does not explain the meaning of many parameters (page, limit, remote, recency, distance, job_type, negative_keywords, etc.) or clarify the structure of the locations object, providing only partial compensation for the missing schema descriptions.

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 action ('Search for jobs') and enumerates the main search dimensions (keywords, locations, titles, companies, categories). It is specific enough to understand the tool's core function, though it does not explicitly distinguish itself from sibling tools like list_categories or lookup_companies.

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 guidance is provided on when to use this tool versus the sibling tools. The description only states what the tool does, not the context in which it is preferred over alternatives or any exclusions.

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