Accept the offer for a job. This is a major state change that closes out the search for this role; confirm with the user before calling. It does not email the employer.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | Job id | |
| confirmed | Yes | Must be true after the user confirms accepting the offer |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| meta | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that accepting the offer is a major state change that closes out the search, going beyond the annotations that only mark destructiveHint=true. It also adds a specific non-behavior (does not email the employer), which is useful context not present in annotations. No contradiction with annotations; it actually enriches them.
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 action, followed by critical warnings and a limitation. There is no fluff or redundancy. Every sentence serves a purpose: defining the action, highlighting the state change/confirmation requirement, and noting what it does not do.
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?
The tool has only two parameters, both fully covered by the schema, and an output schema is present, so return values are not needed in the description. The description covers the key behavioral aspects: the destructive nature, the need for confirmation, and the absence of employer notification. It is complete enough for an agent to invoke correctly, though it could theoretically mention the impact on related job status, but this is adequately implied by 'closes out the search.'
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%: both job_id and confirmed are described in the schema. The description does not add extra parameter-level semantics beyond what the schema already provides, so the baseline score of 3 applies. The description's mention of user confirmation aligns with the confirmed parameter but does not add new information.
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: 'Accept the offer for a job.' It further defines the scope by noting it 'closes out the search for this role,' which differentiates it from other offer-related siblings like decline or create. The verb and resource are specific, and the intent is 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 gives an explicit precondition: 'confirm with the user before calling.' This is a crucial usage guideline for a destructive action. It also provides a negative constraint by stating it does not email the employer, clarifying what the tool does not do. While it doesn't explicitly name alternatives (e.g., decline), the purpose is clear enough to select this tool for acceptance.
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.
