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Performance-Warnungen anzeigen

get_performance_alerts
Read-only

Beantwortet "hat die Überwachung zuletzt etwas gemeldet?" — die OFFENEN Warnungen der laufenden turbometrics-Überwachung (z. B. TTFB über der Schwelle, visuelle Regression, fehlgeschlagener Scan), also Ereignisse über die Zeit, keine Momentaufnahme und keine Messwerte. Die Zahlen einer Messung stehen in get_performance_findings, der zwischengespeicherte Gesamtwert in get_performance_score. Eine leere Liste wird nicht pauschal als Entwarnung ausgegeben: Die Antwort unterscheidet "überwacht, nichts offen", "Domain wird gar nicht überwacht" und "nicht ermittelbar".

Input Schema

NameRequiredDescriptionDefault
domainYesDie Domain, z. B. example.com

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, openWorldHint, destructiveHint=false), so the bar is lower. The description still adds real value beyond them: it explains that an empty list has three distinct meanings ('monitored, nothing open', 'domain not monitored at all', 'not determinable'), which prevents a false all-clear. It does not mention auth, rate limits, or pagination, so it stops short of a 5.

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-loaded with the core question and resource, then sibling routing, then the empty-list caveat — a logical progression with no filler sentences. Dense but every sentence earns its place; the illustrative examples cost a little length but add clarity.

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?

For a read-only, single-parameter tool with no output schema, the description supplies exactly the missing context: what the returned events represent and how to interpret an empty result. Nothing an agent needs to call and interpret this tool correctly is absent.

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?

Only one parameter (domain) with 100% schema description coverage, so the schema already carries the parameter meaning. The description adds nothing about the domain argument beyond what the schema states, so the baseline 3 applies.

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?

Names a specific resource (the OPEN alerts of the running turbometrics monitoring) and verb-like framing ('has monitoring reported anything?'), with concrete examples (TTFB over threshold, visual regression, failed scan). It explicitly distinguishes itself from the two sibling tools get_performance_findings and get_performance_score by stating that it returns events over time, not measurements or snapshots.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Routes the agent explicitly: raw measurement numbers live in get_performance_findings, the cached aggregate in get_performance_score. The opening question frames the use case (checking whether monitoring has flagged anything recently) so the agent knows when to reach for this tool versus its siblings.

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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