Destava job search

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

Annotations already declare readOnly/idempotent/non-destructive, yet the description still adds substantial substance: status semantics including the 30-day closed rule and last-seen date, age in days, repost counts, the long_open/reposted signals, the 600-character excerpt cap, a prompt-injection warning about company-authored text, and a data-retention disclosure. That is behavioral context an agent cannot get from the structured fields.

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 first sentence is front-loaded with the essential identification and the return payload is enumerated compactly. The trailing privacy/retention sentence is long and tangential to correct invocation, which costs a point but doesn't obscure the core instruction.

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 full annotations and an output schema, nothing needed to call it correctly is missing: the accepted identifier forms, what comes back, and the safety caveat on untrusted text are all present.

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 schema description already says "apply_url from search_jobs, or its id (ds:…)", so the description's restatement of the same dual-accept value adds no new meaning. Baseline 3 applies because the schema carries the parameter burden 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 and resource ("One posting ... by the apply_url ... or by its id") and immediately separates it from the sibling search tool that produces the apply_url. An agent can tell this is the single-item retrieval counterpart to search_jobs without opening either 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 implies the call chain — take the apply_url a search returned, or its id — which tells the agent this comes after search_jobs. It stops short of explicit when-not-to-use guidance (e.g. don't loop it over many URLs, use watch_search for ongoing monitoring), so a 4 rather than 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, openWorld and non-destructive, so the safety bar is low, yet the description still adds real behavior: result cap of 20 with relevance ordering, snippet plus company apply link, a prompt-injection warning that titles/snippets are untrusted, pagination mechanics, and a data-retention disclosure. The one gap is that it doesn't say what an empty result set looks like, which matters for an openWorld search.

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?

Four sentences, front-loaded with what is searched and how results are returned, then pagination, then trust and privacy caveats. Every sentence carries information an agent would otherwise have to guess, though the logging/privacy sentence is peripheral to tool selection.

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 an output schema handling return shape, rich annotations covering the safety profile, and 100% schema coverage on all 7 parameters, the description supplies the remaining pieces: corpus scope, semantic matching, paging via next_offset, and untrusted-content handling. Nothing an agent needs in order to call this correctly or safely 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%, so baseline is 3, but the description adds meaning the schema lacks: the query is matched by meaning rather than keyword, so typos and related titles still hit, and it ties next_offset to offset to explain page chaining. The interaction between the documented default limit of 10 and the stated 20-result ceiling is left for the agent to reconcile.

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 ("Searches current job postings") and scopes the corpus to companies' own career sites and ATSs, plus semantic matching. It never names the siblings get_job or watch_search, so an agent must infer the search-vs-fetch-vs-save split from the names 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?

Usage is implied by the corpus description ("current job postings") and made concrete for pagination ("For more, pass next_offset back as offset"), which tells the agent how to continue iterating. There is no explicit when-not guidance or routing to get_job for a single posting or watch_search for recurring searches.

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?

Beyond the annotations, the description discloses the crucial behavioral trait: the tool only produces a link and nothing is set up until the user approves it, which reconciles the readOnlyHint with an apparently stateful action. It also states the data-retention posture (nothing stored for the link, host logs keep IPs up to 7 days), adding privacy context the annotations cannot express.

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 core action is front-loaded in the opening clause, and the following sentences cover the consent flow and retention. Slightly dense, but every sentence contributes a distinct fact; nothing is padding.

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 a full output schema and rich annotations already present, the description only needs to supply the consent flow and storage behavior, which it does. An agent knows what the call returns, what the user must do next, and what is retained.

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 each parameter already carries its own description and examples. The description's only added meaning is that the arguments mirror search_jobs, which is a useful cross-reference but does not extend beyond what the schema documents.

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 specific verb and resource: it builds a destava.com link that turns a search into a recurring daily run on the user's own account. It also grounds the parameters in search_jobs, which helps an agent relate it to the sibling tool, but it never explicitly says 'use this instead of search_jobs when the user wants recurring matches'.

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?

Usage is implied rather than stated: creating a recurring watch is the natural fit, and the two-step handoff (user must open the link, sign in with Google and approve) is spelled out. There is no explicit when-not guidance or direct comparison with search_jobs, so the choice between the two is left to inference.

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