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emailalias

@emailalias/mcp

by emailalias

update_alias_display_name

Schedule a display-name change on an alias (Premium-only). The new name becomes pending and applies after 24h; limited to 3 edits per 24h. Pass null to clear, with rejection of brand-impersonation names.

Instructions

Schedule a display-name change on an alias (Premium-only). Edits do NOT take effect immediately — the new value lands in display_name_pending and promotes 24h after the most recent edit. Editing again resets the clock. Capped at 3 edits per rolling 24h per alias. Pass display_name=null (or empty string) to clear; clearing follows the same cooldown. Brand-impersonation patterns (PayPal, Apple, banks, etc.) are rejected with 400.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
alias_idYes
display_nameYesNew display name, or null to clear. Max 32 characters.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.2

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and delivers: delayed effect with display_name_pending promotion, clock-reset on re-edit, rate limiting, clear-via-null semantics, and a 400 rejection for brand-impersonation patterns. These are exactly the behavioral traits an agent needs to predict side effects.

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?

Front-loaded with the core purpose, and every subsequent sentence adds a distinct operational fact: delay, reset, cooldown, clearing, rejection. 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?

For a mutation with no annotations and no output schema, the description covers prerequisites, timing, rate limits, clearing, and error conditions. The only gap is the success response shape, which is minor for a 2-parameter tool whose side effects are thoroughly described.

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 only 50% (alias_id is undocumented beyond its uuid format). The description compensates substantially for display_name — null/empty clears, clearing follows the same cooldown, brand patterns rejected — which goes well beyond the schema's one-line parameter note. alias_id semantics are left to name and context, but that is low-risk.

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?

States a specific verb and resource: 'Schedule a display-name change on an alias.' The scheduling qualifier distinguishes it from the sibling update_alias, and the Premium-only note adds a scoping constraint. An agent can tell exactly what this tool does without opening the schema.

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 gives clear context: this is for scheduled (not immediate) changes, Premium-only, with a 24h promotion window and a 3-edit rolling cap. It does not explicitly name a sibling as the alternative for immediate changes, but the scheduling semantics make the intended use unambiguous.

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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