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set_slack_preferences

Adjust Slack DM notification settings: mute DMs, toggle event alerts, set quiet hours, or change delivery cadence. View current preferences without arguments.

Instructions

Read or update the caller's Slack DM preferences. Resolves the user via license_key → email, then applies the change across every Slack workspace the email is linked to. Call with no args to see current state. Call with mute: "1h" (or "today", "forever", "off") to silence DMs for a window. Call with eventNewPin: false (or any event_* flag) to toggle individual event types off. Same surface as the App Home toggles and /pincushion mute, accessible from the agent — useful for "mute pin DMs during this refactor" workflows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
muteNoFriendly mute alias. "off" unmutes.
timezoneNoIANA timezone (e.g. America/Los_Angeles) for quiet hours.
digestModeNoDelivery cadence. "instant" is the default; "hourly" and "daily" are reserved for a future digest implementation.
mutedUntilNoAlternative to `mute`: ISO timestamp until which DMs are silenced, or null to unmute.
eventNewPinNoDM on new pins.
eventMentionNoDM on @-mentions of you.
eventFollowUpNoDM on replies in threads you authored or commented on.
eventPinReadyNoDM on pins marked ready for implementation.
eventResolvedNoDM on resolved pins.
quietHoursEndNoQuiet-hours end hour (0-23) in `timezone`.
quietHoursStartNoQuiet-hours start hour (0-23) in `timezone`.
Behavior3/5

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

No annotations provided, so description bears full burden. It discloses that the tool resolves user across all Slack workspaces, but does not mention permissions, idempotency, or side effects beyond the described behavior. Adequate but could be more explicit.

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

Conciseness4/5

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

Well-structured with clear first sentence, then resolution process, then examples. Slightly long but each sentence adds value; no waste.

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?

Handles all parameters with schema descriptions, but no output schema and description does not detail return structure (only mentions 'see current state'). For a tool with 11 parameters, this is a gap in completeness.

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 coverage is 100%, baseline 3. Description adds value by explaining the intent behind parameters (e.g., 'mute is a friendly alias', 'digestMode reserved for future'), enhancing understanding beyond the schema.

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 clearly states 'Read or update the caller's Slack DM preferences', providing a specific verb-resource pair. It distinguishes from sibling tools which focus on pins, replies, and critiques, making this unique.

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?

Provides clear usage examples (with no args, with mute, with event flags) and context ('useful for mute pin DMs during this refactor workflows'). Does not explicitly state when not to use, but covers main use cases.

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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