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List alert deliveries

list_deliveries
Read-onlyIdempotent

Requires the read scope or higher. Lists recent alert deliveries across the project's monitors: whether an alert fired, failed or was suppressed, and to which destination. Each row is one (event, destination) outcome: pending (in flight), delivered, dead (attempt ceiling reached) or suppressed (not sent: the destination's rate cap, or a blocked run answered within the hold; last_error says which). Covers 30 days, newest page only. untrusted_fields names the data fields LastPing did not write (job output, exporter data or user-supplied names).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax deliveries to return (default 20, max 100).
statusNoRestrict to one delivery status: pending, delivered, dead, or suppressed.
monitorNoRestrict to one monitor's deliveries (UUID).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, it discloses the required scope, the 30-day retention window, the newest-page-only pagination limit, and the exact semantics of every status including why a row is suppressed and where last_error points. It also explains untrusted_fields as data LastPing did not write, which is behavior an agent cannot infer from structured fields.

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?

Front-loads the auth requirement and packs retention, granularity, status semantics and untrusted_fields into a compact block with no filler. The heavy parentheticals and semicolons make it dense to parse, but each clause carries distinct information.

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

Completeness5/5

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

With no output schema, the description carries the return-shape burden and does so: it explains that each row is an (event, destination) outcome, enumerates the possible statuses, and interprets untrusted_fields. An agent has everything needed to call it and read the result correctly.

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%, so limit and monitor are already documented. The description adds genuine meaning for status by explaining what each value represents (pending in flight, dead attempt ceiling reached, suppressed for rate cap or blocked run), which the schema only lists as bare values.

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 (lists alert deliveries across the project's monitors) and immediately defines the row granularity as one (event, destination) outcome. No sibling in the toolset covers deliveries, so the scope is unambiguous without needing to name an alternative.

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?

Gives a prerequisite (read scope or higher) and states the practical boundaries: 30-day coverage and newest page only, which implicitly tells the agent it cannot reach older deliveries. It stops short of naming an alternative tool for historical data, so it is clear context rather than explicit when/when-not routing.

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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