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particle_alert_list

Read-only

List the alerts in your project, newest first. Each entry carries the alert id — feed it into particle_alert_get for full configuration, particle_alert_list_matches for what it has caught, or particle_alert_update / particle_alert_delete to manage it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoAlerts per page (1-100, default 25).
cursorNoOpaque pagination cursor from a previous response's cursor field.
output_formatNoOutput serialization. 'markdown' (default) returns the LLM-facing rendering. 'json' returns the structured payload as JSON text — use only for programmatic chaining where exact field extraction matters; the JSON shape is larger and noisier for an LLM to read.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and destructiveHint, so the safety profile is covered. The description adds useful behavioral detail: results are newest-first, each entry carries the alert id, and this is scoped to the current project. This goes beyond the annotations without contradicting them.

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?

Two compact sentences with no filler. The main behavior is front-loaded, and the downstream routing adds high-value guidance without bloating the description.

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 read-only list tool with no output schema, the description gives the essential return clue (each entry carries the alert id) and ordering. It does not enumerate all entry fields, but it provides enough for an agent to decide to call the tool and to chain into the appropriate follow-up tool.

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

Parameters3/5

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

Schema description coverage is 100%, so the input schema fully documents limit, cursor, and output_format. The description adds no parameter-specific details but is not required to; it stays at the baseline because it does not enrich parameter meaning 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 the operation ('List the alerts in your project'), the resource, and the ordering ('newest first'). It also distinguishes itself from sibling tools by explaining what each entry's id can feed into, making it easy to tell apart from particle_alert_list_matches and particle_alert_get.

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 clearly establishes the listing use case and tells the agent what to do with the returned alert ids, routing to get, list_matches, update, or delete. It does not explicitly state when not to use this tool versus create or preview, but the intended context is clear enough.

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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