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datadog_events_list

Retrieve Datadog events from the event/alert stream, filtered by tags, sources, or query, and limited to a time range with pagination support.

Instructions

List Datadog events from the event/alert stream (e.g. deploys, monitor alerts), optionally filtered (e.g. service:api) over a time range (default last 1h). For application log lines use datadog_logs_search instead. limit of 0 (or omitted) auto-paginates across cursor pages up to 10000; any non-zero value caps the total at that count (default 100). from / to accept relative shorthand (15m, 1h), now, RFC 3339, or Unix epoch seconds. Read-only. Mirrors omni-dev datadog events list. Output is YAML.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd of the time range, same formats as `from`. Defaults to `now`.
fromNoStart of the time range. Accepts relative shorthand (`15m`, `1h`), `now`, RFC 3339, or Unix epoch seconds. Defaults to `1h`.
tagsNoComma-separated list of `key:value` tags, e.g. `env:prod,team:sre`. Optional.
limitNoMaximum events to return. `0` means "fetch every match across pages (capped at 10000)"; any non-zero value caps the total at that count, paginating underneath as needed. Defaults to 100.
filterNoDatadog events query (e.g. `service:api`). Optional; omit to match all events in the window.
sourcesNoComma-separated list of source names, e.g. `github,nagios`. Optional.
Behavior5/5

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

Discloses read-only nature, pagination behavior (limit=0 auto-paginates up to 10000), time range formats, and output format (YAML). Mirrors CLI command. Comprehensive given no annotations.

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?

Four sentences, front-loaded with main purpose, no extraneous information. Efficiently communicates key details.

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?

Covers all necessary aspects: purpose, filtering, time range, pagination, output, read-only, and sibling distinction. Complete for a list tool with no output schema.

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 already describes all 6 parameters, but the description adds valuable context like limit=0 auto-paginates, from/to format examples, and tags as comma-separated. Exceeds schema coverage.

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?

Clearly states it lists Datadog events from the event/alert stream, with examples like deploys and monitor alerts. Distinguishes from sibling tool datadog_logs_search by specifying it is for log lines.

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?

Explicitly directs to use datadog_logs_search for application log lines instead. Explains pagination behavior and defaults. Could be improved by listing more specific use cases, but sufficient.

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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