Undo an auto-applied inbox action. This can delete a board record that the automatic action created, so confirm with the user first.
| Name | Required | Description | Default |
|---|---|---|---|
| item_id | Yes | Inbox item id | |
| confirmed | Yes | Must be true after the user confirms undoing the automatic action |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| meta | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as destructive, and the description adds specific, valuable behavioral detail: the undo operation can delete a board record created by the automatic action. It also communicates the safety requirement to confirm with the user, going beyond what the annotations alone provide.
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 tight sentences deliver the purpose, the destructive consequence, and the required user-confirmation ritual. Information is front-loaded: the main action appears first, followed by the critical warning. There is no filler.
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?
Given the tool's moderate complexity, the annotations, and the presence of an output schema, the description covers the essential behavioral contract: what it undoes, what can be deleted, and the confirmation requirement. It does not elaborate on edge cases or results, but the existing schema and annotations cover enough for confident 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?
The input schema fully documents both parameters, so the baseline is 3. The description adds extra meaning by tying the confirmation requirement to the user-confirm step and clarifying the real-world consequence of the item_id operation: deleting a board record. This reinforces the schema's parameter semantics rather than merely repeating them.
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 a specific verb ('Undo') and resource ('an auto-applied inbox action'), and then adds a concrete operational effect: it can delete a board record the action created. This distinguishes it from related inbox tools like inbox.dismiss or inbox.decline, and makes the tool's purpose immediately understandable.
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 clear context: this tool is for undoing auto-applied inbox actions, not manual ones, and it explicitly instructs to confirm with the user first. It does not name alternative tools or exclusion cases, but the usage context is clear enough for an agent to select it appropriately.
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.
