Scrape job results
scrape_job_leadsLeads produced by a finished scrape job, capped at 200 rows per call.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Rows to return, max 200 | |
| job_id | Yes | Job id |
scrape_job_leadsLeads produced by a finished scrape job, capped at 200 rows per call.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Rows to return, max 200 | |
| job_id | Yes | Job id |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds a useful behavioral constraint: only finished jobs yield leads, and results are capped at 200 rows per call. It does not address failure modes or pagination, but for a simple read operation this is acceptable.
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 compact sentence with no filler, front-loading the key facts: leads, finished job, and the 200-row cap. Every word contributes useful 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?
For a two-parameter, read-only tool with full schema coverage and strong safety annotations, this description is adequate. The agent learns the precondition, the relevant resource, and the row limit; no output schema exists, so return details are not required.
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. The description adds meaning by tying job_id to a 'finished scrape job' and characterizing limit as a per-call cap, which goes slightly beyond the bare schema descriptions.
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 identifies the resource as leads from a completed scrape job and notes the 200-row cap, which helps distinguish it from scrape_job_status and scrape_leads_start. However, it is phrased as a noun phrase rather than an explicit verb like 'get' or 'list', so it is clear but not maximally strong.
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 'finished scrape job' implies the tool should be used after a scrape completes and the caller wants the resulting leads. It does not explicitly reference siblings such as scrape_job_status for checking completion or scrape_leads_start for initiating a job, so the guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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