AnywhereRoles remote jobs

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the agent knows this is a safe, repeatable read. The description adds only the rough payload contents; it says nothing about auth, rate limits, or behavior for unknown slugs, which is acceptable given annotation coverage 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?

One tight sentence that leads with the action and parameter source, then the returned data. No filler; every clause carries 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?

With no output schema, the description usefully names the kind of data returned (job count, categories, tags), which is what an agent needs for a single-parameter read tool. Minor omission: it doesn't note behavior for a missing slug, but overall it is complete enough.

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% and the schema already gives the origin and an example ('gitlab') for slug. The description restates the same provenance for the single parameter, adding no syntax or format detail beyond the schema. 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 and resource (get a company's profile) scoped by slug, and enumerates the returned payload (open remote job count, top categories, tags). It explicitly references list_companies, so an agent can tell it apart from the sibling that enumerates 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 phrase 'by slug (from list_companies)' implies the workflow — fetch the slug from list_companies first, then call this — which is useful routing. However, there is no explicit when-to-use/when-not statement or named alternative for other lookups, so usage is only implied.

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, destructiveHint=false and openWorldHint, so the safety profile is covered. The description adds real value by disclosing that the full description is not returned inline and lives at the posting URL, which shapes how the agent should treat the result.

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 dense sentences with zero filler; the core action and return fields are front-loaded, followed by the ID provenance and the URL caveat. Every clause 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 tool with no output schema and annotations covering safety, the description is complete: it identifies the input source, the fields returned, and where the omitted content lives.

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% and the single id parameter is documented as 'Job ID from search_jobs'. The description merely restates the same provenance, adding no extra syntax, format, or validation detail 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?

States a specific verb (get) and resource (one job listing by ID) and enumerates the returned fields, distinguishing it clearly from list/search siblings. An agent can tell it fetches a single job given an ID rather than searching or listing companies/tags.

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?

Explicitly tells the agent where the required ID comes from (search_jobs), which is the key usage precondition. It does not state when-not to use it or name alternative siblings, so it falls short of a full 5.

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 readOnly, idempotent, non-destructive and open-world behavior. The description adds real context beyond them: the values are advertised (not actual) salaries, restricted to remote jobs, and denominated in USD. It says nothing about aggregation windows, freshness, or pagination.

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; the optional-category caveat is appended efficiently. It is terse rather than padded, though it errs slightly toward under-specification.

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 read-only, zero-required-parameter insights tool with no output schema, the description conveys scope (remote, USD, by category) adequately. An agent could still want to know the shape of the returned ranges and whether it is a global or per-category aggregate, but nothing essential to invocation 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 coverage is 100% and the single parameter's description points to list_categories, so the schema does the heavy lifting. The description's "optionally for one category" merely restates optionality already encoded by the empty required list.

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 resource (advertised salary ranges) and narrows it to remote jobs in USD by category, which is more precise than the bare tool name. It lacks an explicit verb (list/retrieve), but the noun phrase unambiguously describes the payload. Sibling get_statistics could plausibly overlap, and nothing here distinguishes them.

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?

"optionally for one category" tells the agent the parameter is optional but gives no when-to-use guidance relative to get_statistics or the other retrieval tools. There is no statement of prerequisites or exclusions.

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, openWorldHint and destructiveHint=false, so the safety and repeatability profile is covered. The description adds only the 'right now' freshness cue, which is mildly useful, but says nothing about cost, rate limits, or how the aggregates are computed.

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 names the resource and then lists the contents. No filler, no repetition of the title or name.

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 no parameters and no output schema, the description carries the burden of telling the agent what comes back, and it does so in outline (counts, salaries, trends). It is nearly complete for this complexity, though the lack of any scoping note (e.g. global vs filtered) leaves a small gap.

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 takes zero parameters, so there is nothing for the description to disambiguate; the baseline is 4. The description does usefully name the categories of output, although parameter semantics are not at issue here.

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 (aggregate) and resource (remote job market statistics) and enumerates what is included: open job counts, salary figures, trends. It does not, however, differentiate itself from the sibling get_salary_insights, so an agent cannot tell the two apart on description alone.

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 statement of when to use this tool versus alternatives such as get_salary_insights or search_jobs, and no prerequisites or exclusions are given. The overlap with get_salary_insights is precisely the case where routing guidance was needed most.

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 useful context that the return values are IDs intended as filter inputs, but says nothing about ordering, pagination, or completeness of the list. With annotations carrying the safety burden, 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 sentence that front-loads the resource and immediately states the practical purpose. No filler, no redundancy with the title.

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?

There is no output schema, but the description compensates by stating what is returned (category IDs) and what those IDs are for. For a trivial no-param list tool with full annotation coverage, nothing an agent needs 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 tool takes zero parameters, so there is nothing for the description to disambiguate. Baseline for a no-parameter tool is 4; the description correctly implies a simple unconditional listing.

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+resource ('List job categories') and goes further to name the exact field returned ('their IDs'). It also names the siblings that consume that output, so the agent can immediately tell what this tool is for relative to the rest of the set.

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 explains the downstream purpose — supplying the categoryId filter for search_jobs and get_salary_insights — which effectively tells the agent when to call this tool (before filtering by category). It does not explicitly say when NOT to use it, but there is little ambiguity given it is a lookup list.

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 readOnly, idempotent, non-destructive, open-world behavior, so safety is covered. The description adds value beyond them by disclosing the return shape (slugs intended for get_company), enabling correct tool chaining. It does not mention pagination limits, total counts, or rate limits, keeping it from a 5.

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 tight sentence that front-loads the core action and follows with the filter and return value. Every clause carries information; nothing is redundant or padded.

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 three-parameter read-only listing tool with no output schema, the description covers purpose, optional filtering, and return type. It omits pagination behavior (default size, 0-indexed pages) and how many companies exist, but those gaps are minor given the fully documented schema and safety annotations.

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 page, size, and query are already fully documented in the schema. The description only restates the optional name filter and adds nothing about pagination or the 1-50 size bound, so the baseline of 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 (list) and resource (companies) with a qualifying scope (open remote jobs), and contrasts with the sibling get_company by noting it returns slugs for that tool. An agent can distinguish it from search_jobs, list_categories, and get_company without opening any schema.

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?

Clearly states the filter is optional and names get_company as the downstream tool that consumes the returned slugs, which gives concrete usage context. It stops short of explicit when-not-to-use guidance or naming an alternative listing tool, so it is not a full 5.

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?

The annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is fully covered. The description adds the domain scope (skill/technology tags on job listings) and states that IDs are returned, but says nothing about volume, ordering, pagination, or whether the tag set is fixed or user-specific.

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 states the resource first and then clarifies scope with concrete examples. No filler, no repetition of the title.

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 listing tool with no output schema, the description adequately covers what is returned (tags plus their IDs) and what domain they belong to. It could be marginally stronger by noting the tag taxonomy or how the IDs are used, but nothing essential for invoking 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?

The tool takes zero parameters, so the baseline is 4 and there are no parameter semantics the description needs to compensate for. Nothing in the description misrepresents the (empty) input surface.

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 gives a specific verb (List) and resource (skill and technology tags on job listings), and the parenthetical examples (React, Python, Figma) pin down exactly what 'tag' means. It does not explicitly distinguish itself from the sibling list_categories, which an agent might reasonably confuse it with, so it stops short of a 5.

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 explicit statement of when to use this tool versus alternatives such as list_categories or search_jobs, and no prerequisites or exclusions. Usage is only implied by the mention of returning tag IDs, which hints at a filter/lookup role.

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, non-destructive semantics, and the description adds behavior not in those annotations: deduplication across sources, reposts hidden by default, and that results point to the original posting URL where the user applies. This is meaningful operational context beyond the annotation set.

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 tight paragraph, front-loaded with what the tool searches, followed by the two parameters worth explaining and the return shape. No filler sentences.

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 no output schema, the description helpfully enumerates return fields (title, company, location, salary, eligibility, original URL) and covers default hiding of reposts. For a 15-parameter tool it doesn't touch pagination behavior or most boolean filters, but the schema documents those fully, so coverage is adequate.

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 baseline is 3; however the description adds semantics the schema lacks, explaining that overlapWith ranks by working-hours overlap and that eligibleFrom restricts to country-eligible jobs, which clarifies the intent of those two parameters rather than merely restating them.

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 (search) and resource (open remote job listings) with scope: aggregated from many boards, deduplicated. The aggregate/deduplicated framing distinguishes it from get_job and list_companies explicitly enough for an agent to route correctly.

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 concrete usage context for eligibleFrom (country eligibility filtering) and overlapWith (time-zone overlap ranking), plus the default behavior on aggregator reposts. It does not name sibling alternatives (e.g. when to prefer list_categories before passing categoryId, or get_job for a single listing), so it stops short of explicit when-not guidance.

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