Refine Job Search

inbox.list

Read-onlyIdempotent

List email conversations Refine matched to your job search (applications, interviews, recruiter outreach)

Input Schema

TableJSON Schema

Name	Required	Description
`tab`	No	Which inbox tab to list; defaults to applications
`page`	No	Pagination cursor returned as meta.next_page
`limit`	No	Maximum records to return
`shelf`	No	For the outreach tab: show the low-signal shelf instead of the main feed
`status`	No	pending needs a decision, auto was auto-applied, active has an open conversation, handled is done
`unread`	No	With status=active: only conversations with (or without) an unread reply
`account`	No	Filter to one connected Google account id

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	Yes
`meta`	No

TDQS

B3.3/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that conversations are filtered to job search, but doesn't disclose pagination or ordering behavior. No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence that front-loads the action and scope. No filler or redundant phrasing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The schema and output schema cover parameters and return format, so the description is not required to repeat them. However, it lacks any usage guidance and doesn't highlight key filter options, making it only minimally complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers 100% of parameters with descriptions. The description only mentions the tab categories, which are already in the schema, so it adds no extra meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('List') and resource ('email conversations') with a clear scope: 'matched to your job search' and enumerates categories (applications, interviews, recruiter outreach). It doesn't explicitly contrast with sibling tools, but the listing vs. fetching distinction is implicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives like inbox.get or inbox.refresh. The description only states what it does, not the context for selecting it.

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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TDQS

A3.6/5.0

Disambiguation4/5

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.

Naming Consistency5/5

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.

Tool Count2/5

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.

Completeness5/5

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.

Resources

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