Fixter

describe_alerting

The static measure catalog for authoring an alert rule: per source (LOGS, SPANS, METRICS), the measure functions available, each with its unit and defaultMode (THRESHOLD or ANOMALY — the mode a new rule on this measure should default to). READ: available to any authenticated user. This is a static catalog: it reads no telemetry and returns the same answer for every caller.

Call query's describe_schema first for the tenant's services, groupable fields, and metric names (pass source=metrics for the metric list) — this tool no longer returns any of that. Use this tool only to pick a measure once you know the source and, for METRICS, the metric's kind.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A5/5.0

Behavior5/5

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

The description discloses key behavioral traits beyond any annotations: it's a static catalog (reads no telemetry), returns the same answer for every caller, and is available to any authenticated user. Since no annotations are provided, the description fully covers the behavioral burden.

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?

The description is well-structured and front-loaded with the core purpose. The extra guidance about the alternative tool and usage order is provided in a separate sentence, making it easy to scan. No wasted words.

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 tool with zero parameters and no output schema, the description is exceptionally complete. It explains what the tool returns, its behavior (static), its access level, and how it relates to sibling tools. No gaps remain.

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

Parameters5/5

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

The input schema has zero parameters and the schema description coverage is 100%, so there is nothing for the description to add about parameters. The description explains why no parameters are needed and provides all necessary context about what the tool returns.

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 tool returns the static measure catalog for authoring alert rules, per source (LOGS, SPANS, METRICS), including measure functions, units, and defaultMode. It distinguishes itself from siblings like describe_schema and query's describe_schema by explicitly stating it no longer returns tenant services, groupable fields, or metric names.

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?

The description provides explicit guidance: call query's describe_schema first to get tenant services, groupable fields, and metric names, then use this tool only to pick a measure once you know the source and, for METRICS, the metric's kind. This clearly tells when to use it versus alternatives.

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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TDQS

A3.8/5.0

Disambiguation2/5

Several tool pairs are near-duplicates, including three deprecated aliases (add_investigation_alert_channel vs add_alert_channel, list_investigation_alert_channels vs list_alert_channels, remove_investigation_alert_channel vs remove_alert_channel) that muddy the surface. Additionally, suppress_signal and create_ignore_rule both suppress alerting via different mechanisms, which could cause misselection despite detailed descriptions.

Naming Consistency4/5

The vast majority of tools follow a clear verb_noun snake_case pattern (create_api_test, list_issues, set_alert_rule_status). A few bare-noun tools (logs, spans, metrics) and the standalone verb correlate break the pattern slightly, but overall the naming is highly consistent and predictable.

Tool Count1/5

With 52 tools, this is on the extreme end of the calibration scale. Even accounting for the broad scope of an observability platform, the count is excessive and includes several deprecated redundancies that inflate it further.

Completeness5/5

The toolset provides comprehensive CRUD/lifecycle coverage across all major domains: alert rules (create, read, update, delete, status, delivery, preview), API tests (create, read, update, delete, run history, credentials), ignore rules and suppressions, issues with digest config, investigations with claim/read, channels, credentials, and rich query tools (logs, spans, metrics, SQL, traces, correlation). No obvious dead ends or missing core operations.

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