Queue a job posting to be re-scraped. The returned job may remain pending; use jobs.get later to inspect the refreshed state.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | Job id |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| meta | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate this is a mutation (readOnlyHint=false) and not idempotent, but the description adds key behavioral context: the operation is asynchronous ('may remain pending') and requires polling via jobs.get. This goes beyond what annotations provide, clarifying the eventual consistency and the way to obtain results. No contradiction with annotations.
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 concise sentences that lead with the core action and immediately provide the critical asynchronous behavior and follow-up step. There is no unnecessary detail, and the structure is front-loaded for quick comprehension.
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 queueing tool with a well-covered schema and existing output schema, the description sufficiently conveys the operation's async nature and how to verify results. It does not cover potential error states or edge cases, but these are not essential for correct invocation. Given the tool's simplicity, this 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?
The schema already describes job_id as 'Job id' with 100% coverage, so the description adds little about the parameter. It indirectly associates job_id with the 'job posting' being re-scraped, but this is also evident from the tool name. The baseline of 3 is appropriate since the schema handles parameter documentation.
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 tool's purpose: 'Queue a job posting to be re-scraped.' This specifies the action (queue a re-scrape) and the resource (job posting), distinguishing it from siblings like jobs.delete, jobs.archive, and inbox.refresh. The resource and intent are unambiguous.
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 tool is for triggering a re-scrape but does not explicitly state when to use it versus alternatives, nor any exclusions. It does give a follow-up instruction—'use jobs.get later to inspect the refreshed state'—but that is post-usage guidance rather than selection criteria. No alternatives or when-not-to-use conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tools are largely distinct due to the domain-prefixed naming (inbox, jobs, signals, etc.) and detailed descriptions. While there is some overlap among inbox actions like acknowledge, apply_suggestion, and decline, the descriptions clarify each behavior. The signals and recommendations sub-groups also have clear boundaries, making misselection unlikely.
All tools follow a consistent pattern of domain.entity.action or domain.action (e.g., inbox.list, jobs.interviews.add, signals.recommendations.dismiss). This uniform camelCase-with-dots convention makes the set highly predictable and easy to navigate.
At 55 tools, the server far exceeds the 25-tool threshold for 'too many' as per the calibration. While the broad domain of job search management justifies numerous operations, the count is still overwhelming and could overwhelm agents or cause selection errors. Several signal-related tools could potentially be consolidated without compromising functionality.
The tool set covers the full lifecycle of job applications: inbox management (list, get, draft, send), job tracking (add, update, archive, delete), interviews (add, update, delete), offers (create, update, accept, decline, negotiation), and company signals (track, pause, recommend, block). There are no obvious missing operations for the core workflows.
