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inbox.decline

Destructive

Queue decline replies to recruiter outreach. Depending on the user's preference this SENDS email from their address. Only call after the user explicitly approved declining these specific conversations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsYesInbox item ids to decline
rememberNoSave the preference for future declines
confirmedYesMust be true, and only after the user explicitly approved declining these conversations
preferenceNoSend preference to apply; omit to use the saved preference

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
metaNo

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already mark this as destructive (destructiveHint=true) and non-read-only (readOnlyHint=false), and the description adds meaningful context beyond them: it queues replies and 'SENDS email from their address' depending on preference, a real external side effect the agent must communicate to the user. This external-sending behavior and the conditional dispatch are genuinely informative additions. No contradiction with annotations exists.

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?

Three short sentences, each earning its place: tool purpose, the critical email-sending behavior, and the consent precondition. The purpose is front-loaded and there is no filler or repetition of schema content.

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

Completeness4/5

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

With an output schema and annotations that already cover return values and the destructive/write profile, the description covers the essential operational facts: queuing behavior, potential external email dispatch, and the explicit-approval gate. The only residual gap is ambiguity about whether declined replies are sent immediately or held for review, and the precise semantics of the preference enum values.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3, but the description adds value by tying the preference parameter to its behavioral consequence — 'Depending on the user's preference this SENDS email from their address' — which the bare enum cannot convey. It also reinforces the confirmed parameter's role as an explicit approval gate. The exact meaning of each enum value (always/review/never) is still left to inference, so it stops short of a 5.

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

Purpose5/5

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

The description names a specific verb and resource — 'Queue decline replies to recruiter outreach' — which makes the tool's function unmistakable and distinguishes it from siblings like inbox.send_reply, inbox.draft_reply, and inbox.dismiss. The added disclosure that it may send email from the user's address further separates it from non-sending actions such as inbox.mark_read or inbox.acknowledge.

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

Usage Guidelines4/5

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

The description provides an explicit invocation precondition: 'Only call after the user explicitly approved declining these specific conversations,' which properly gates a consent-sensitive operation. However, it names no sibling alternatives and gives no when-not-to-use guidance, so routing among inbox.dismiss and inbox.unsubscribe is left to the agent's inference.

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.

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