Curaiz Remote Jobs

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

Annotations already establish read-only, idempotent, and non-destructive behavior. The description adds meaningful behavioral context: results are ordered by semantic similarity, are compact, and never include full job descriptions. This helps set expectations about output shape beyond what annotations cover.

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 three sentences with no filler. It front-loads the primary purpose, then gives the most important usage nuance, and ends with a concise behavioral caveat. Every sentence contributes useful 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?

Given the rich input schema, annotations, and an output schema, the description covers the core behavioral contract: what is searched, how incremental search works, and what results will look like. Nothing essential for invoking the tool correctly is 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 schema already documents all parameters with 100% coverage, so this is near a baseline of 3. The description adds extra value by explaining the incremental-search contract around `since` and `searched_until`, which is not fully derivable from the schema 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?

The description opens with a specific action and resource: 'Find remote jobs ordered by semantic similarity to an ideal job description.' This clearly conveys what the tool does and its core behavior. It is distinguishable from the sibling tools like get_job_details, since the scope is job search rather than detail retrieval.

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 usage guidance for the `since` parameter: omit it for the full corpus and pass `searched_until` for incremental searches. It stops short of explicitly naming sibling alternatives and the conditions for choosing them, though the note that results never include full job descriptions implies when get_job_details would be relevant.

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 establish read-only, idempotent, and non-destructive behavior, so the description does not need to repeat them. It adds useful context by disclosing that descriptions and requirements are bounded to keep responses manageable, a behavioral trait not visible in the schema or 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?

Two short sentences front-load the action, resource, and cardinality, then add the response-bounding caveat. There is no filler or repetition of schema or annotation content.

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 one fully documented parameter, an output schema, strong read-only annotations, and a clearly scoped purpose, the description covers what an agent needs to call the tool correctly. The only minor gap is explicit sibling routing, but that is not essential for this simple retrieval tool.

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 fully documents the sole parameter with type, min/max length, min/max items, and a description. The description only restates the 1-3 range and adds the 'Curaiz' brand context, so the schema remains the primary source of parameter meaning.

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 exact action ('get full details'), resource ('Curaiz job slugs'), and cardinality ('one to three'). This clearly distinguishes it from discovery-focused find_recent_jobs and location-focused get_locations.

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 implies the tool is for retrieving details when job slugs are already known. It does not explicitly route to find_recent_jobs for discovery, but the context is clear enough that an agent can infer the intended use.

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 (readOnlyHint=true, idempotentHint=true, destructiveHint=false). The description adds a useful detail — the taxonomy is hierarchical and includes exact names and slugs — but does not reveal additional behavioral traits such as formatting or limitations. This is acceptable given annotation coverage.

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 that conveys all essential information without redundancy. Every phrase earns its place, making it easy for an agent to parse quickly.

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-only lookup that has an output schema, the description fully communicates what the tool returns. The presence of an output schema removes the need to explain return values in prose, and the description covers the key selection context.

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 schema coverage is trivially complete. The description correctly avoids mentioning parameters because none exist, earning the baseline score of 4 for zero-parameter tools.

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 a well-defined resource ('hierarchical applicant-location taxonomy supported by Curaiz job search'), and further clarifies the output includes 'exact names and slugs.' This clearly distinguishes it from the sibling job-focused 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 provides clear context that this tool retrieves location taxonomy for Curaiz job search, making it obvious when it should be used. It does not explicitly mention alternatives or exclusions, but the distinct resource and sibling set make confusion unlikely.

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