Decline the offer for a job, a major state change; confirm with the user first. It does not email the employer.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | Job id | |
| confirmed | Yes | Must be true after the user confirms declining the offer |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| meta | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true and idempotentHint=true. The description adds valuable context beyond annotations: that it is a major state change, requires user confirmation (not captured in annotations), and explicitly states it does not email the employer. This gives the agent a clearer picture of side effects without contradicting the 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 a single, efficient sentence that front-loads the primary purpose, then adds the confirmation requirement and a key side effect. Every phrase contributes useful information with zero redundancy.
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 mutation tool with an output schema and two parameters, the description covers the essential aspects: purpose, confirmation requirement, and a notable side effect. It does not mention the exact output, but the output schema exists. The idempotent behavior is already in annotations, so nothing critical is missing for correct invocation.
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 the schema already explains both parameters: job_id and confirmed. The description adds no additional meaning about parameters. Baseline 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 this tool declines a job offer, a distinct action from accepting or deleting an offer. It uses a specific verb (Decline) and resource (offer for a job), and the addition of 'major state change' reinforces its purpose as a consequential action.
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 includes a critical prerequisite: 'confirm with the user first'. However, it does not explicitly state when to use this tool versus alternatives like accepting, deleting, or negotiating the offer. The sibling names imply the context, but explicit guidance is missing.
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.
