CuratorSearch

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

No annotations are present, and the description does not disclose side effects, read-only nature, authentication needs, rate limits, or error behavior. The payload is a simple retrieval, but the lack of explicit behavioral transparency leaves gaps.

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 succinct, with two sentences that convey the core functionality and the source of the slug. No redundant information or unnecessary detail is present.

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 one-parameter read operation, the description is mostly complete. It explains the input and the output scope (full listing details). It lacks explicit return schema or error handling details, but these are not critical for basic usage and the description covers the essential 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 only parameter, slug, is explained as coming from a curatorsearch.com URL pattern, which gives useful context. However, the schema has no description for the parameter, and the tool description does not specify format constraints, requiredness, or behavior for invalid 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 that the tool retrieves a single job listing in full, including description, salary, deadline, and original URL. It also specifies the input is a slug from a known URL pattern, which distinguishes it from sibling tools like search_jobs or institution_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 implies usage when a specific slug is available, but does not explicitly state when to prefer this tool over alternatives such as search_jobs or institution_jobs. No direct comparison or conditional guidance is provided.

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, the description carries full responsibility for behavioral disclosure. It implies the data is current ('currently has open') but does not state whether the operation is read-only, what happens if the institution is not found, whether results are paginated, or what the return format looks like. Minimal disclosure beyond the core action.

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 concise sentence, which is appropriately short for a simple tool. It front-loads the core action and filter. However, the phrase 'on the board' is jargon that may confuse; a slightly more explicit phrase like 'on the job board' would improve clarity without much length.

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 one-parameter read tool, the description gives the essential purpose and parameter meaning. But it omits any usage guidance, behavioral details (e.g., response shape, error behavior), and the meaning of 'board' is ambiguous. Given no annotations or output schema, the description is minimally complete but leaves room for misinterpretation.

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 clarify the parameter. It says 'by institution name,' which tells the agent that the 'institution' string is the name of the museum or gallery. This adds meaning beyond the bare schema, but it lacks format examples or any note on required format (e.g., exact name vs partial match).

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 the verb implicitly (listing roles) and the resource (open roles for a museum/gallery), filtered by institution name. It is clear enough to distinguish from search_jobs (which likely searches across institutions) and get_job (which likely fetches a specific role), though it doesn't explicitly name these alternatives.

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 on when to use this tool versus siblings. The description does not mention search_jobs, get_job, or salary_transparency, nor does it state conditions under which this tool is preferred. An agent would have to infer that this is the right choice when the institution is already known.

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, the description carries the full burden. It does disclose that the figure is 'computed live' and specifies the exact output values (count and median). However, it does not mention read-only status, data freshness caveats, authentication requirements, or any limitations, leaving some behavioral context undisclosed.

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 sentence that packs in the core output, the population of postings, and the live-computation trait with no filler. It is front-loaded with the headline question and remains readable despite the appended archive-name clause.

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 parameterless aggregate, the description adequately covers what is computed and the output values. The only minor gap is that it does not state whether the result is a formatted string, a single number, or a structured object, but the absence of an output schema makes this a small omission rather than a critical one.

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 empty schema is fully complete. The description adds no parameter-level detail, but none is needed; the baseline of 4 applies because there is nothing for the description to compensate for.

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 metric (count of live postings with salary and median advertised salary) and a specific resource (the CuratorSearch Curatorial Pay Archive headline number). This is clearly distinct from sibling tools like get_job, institution_jobs, and search_jobs, which retrieve individual or filtered job data rather than aggregate pay statistics.

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 guidance on when to use this tool versus the sibling tools. An agent must infer from the aggregate nature of the description that this is for headline pay statistics rather than job lookup or search, but no when-to-use or when-not-to-use conditions are stated.

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, the description must carry the behavioral burden. It discloses the return count limit, ordering (newest first), and that each result links to a curatorsearch.com page, but it omits any mention of authentication, rate limits, or side effects. Since it's a search, read-only behavior is implied but not stated; this is a moderate disclosure.

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 two sentences, front-loaded with the core purpose, and contains no filler. Every clause adds information (source, frequency, limit, ordering, link format). It is appropriately sized for the tool's simplicity.

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 4 parameters (2 with enums), no output schema, and no annotations, the description is incomplete. It does not explain parameter usage, return field details, or pagination behavior. The mention of 'curatorsearch.com page' is vague, leaving agents uncertain about the structure of each result. This tool needs more contextual detail to be called 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 only 25% (only 'query' has a description). The description does not explain any parameters, such as how 'limit' caps results, what 'region' and 'category' filter on, or how they interact. This is a significant gap; the description should compensate for the missing schema descriptions but does not.

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), the resource (museum/gallery/curatorial job listings), and provides specifics like daily gathering, limit of 20, and ordering. It does not explicitly differentiate from sibling tools like institution_jobs or get_job, but the scope is clear enough for an agent to infer its role.

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 no guidance on when to use this tool versus alternatives. It does not mention when to choose search_jobs over institution_jobs (for a specific institution) or get_job (for a single job), nor any exclusions or prerequisites. An agent is left to guess the appropriate context.

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