Relomote

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint=false), so the bar is lower. The description adds a behavior not captured anywhere else: closed jobs are excluded from results, which is a meaningful expectation-setting detail. It does not discuss pagination or description truncation depth beyond 'the start of the description'.

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?

It is effectively one front-loaded sentence: purpose first, field inventory in the middle, usage condition last. The field enumeration is somewhat verbose given an output schema exists, but each clause carries information and nothing is repeated.

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?

An output schema exists, so explaining return values is technically unnecessary, yet the description's field list and the closed-jobs exclusion give a complete picture of a simple two-parameter read tool. Nothing an agent needs in order to invoke it 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?

Schema description coverage is 100%, so the schema already documents both parameters, establishing a baseline of 3. The description reinforces that job_id accepts an id or a relomote.com URL but says nothing about the optional 'board' enum parameter, so it adds little 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 precise verb+resource ('Get one Relomote job by its id or Relomote URL') and then enumerates the returned fields, so the agent knows exactly what it retrieves. It is clearly distinguishable from the sibling search_jobs, which returns multiple matches rather than one 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 specifies the triggering condition ('for when the person asks about a specific job'), which is the right routing signal versus searching. It never names search_jobs as the alternative for finding an id, relying on the schema note instead, 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?

Annotations already establish the read-only, idempotent, non-open-world safety profile, so the burden is lighter. The description adds genuinely non-obvious behavior: results are newest-first, capped at 10 per call, a search spans at most 3 pages, and each hit is a link rather than the full listing.

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 the core purpose, then board semantics, then output shape and pagination caps. It is dense but each sentence carries distinct information; the country/region/worldwide explanation is slightly verbose but justified by the non-obvious filtering rule.

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?

Output schema exists, so return structure need not be re-explained, yet the description still covers ordering, per-call cap, and total page limit. Remaining gaps are minor: no explicit routing to get_job for full listing detail, and no note on what happens when page exceeds 3.

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 71% and the description meaningfully extends it — board semantics, what 'location' means on each board, that 'worldwide' applies to the remote board only, and that visa_sponsorship implies the relocation board. Query and category semantics are left to 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?

States a specific verb and resource ('Search live job listings on Relomote') plus the data provenance ('collected from company career pages'). It distinguishes the two boards clearly, and the mention that results link to a Relomote page where the listing is read implies the boundary with the get_job sibling, though that sibling is never named outright.

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 real selection logic between the two board values, including the subtle case that a country search also surfaces jobs open to its region and worldwide. It stops short of explicit when-not guidance (e.g. when to omit query, or when to call get_job instead for full listing details).

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