remote_jobs_aggregator

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

With no annotations, the description carries the full burden and does disclose meaningful behavior: results are merged and de-duplicated across feeds, billing hits the caller's own Apify account at ~$0.001/job, and the schema adds that bad board slugs return an error row instead of failing. It stops short of covering rate limits, runtime, or partial-failure semantics, but the billing and de-dup disclosures go well beyond 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?

Two sentences, front-loaded with the core action and resource before the pricing note. No filler, no repetition of schema content, and 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 6-parameter, all-optional aggregation tool with no annotations and no output schema, the description covers the source set, the de-duplication/row model, the returned fields, and the cost model — enough for an agent to call it correctly. Minor gaps remain around failure modes and result volume, but those are largely covered by the schema.

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 every parameter (maxJobs, sources, keywords, ashbyBoards, greenhouseBoards, postedWithinDays) is already fully documented in the schema, including examples and edge-case behavior. The description adds no additional parameter semantics beyond restating the aggregated fields, 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 (merge and de-duplicate) applied to a specific resource (remote job listings) from three explicitly named sources, and describes the output shape (one clean row per job with title, company, salary, tags, apply link). No sibling tool overlaps this function, and an agent can tell exactly what it produces.

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 the use case (aggregating remote job feeds) and gives useful cost/billing context, but never states when to use it versus alternatives or when not to use it (e.g. vs. a single-source scraper). Usage is inferable rather than directed.

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