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list_alert_channels

List the authenticated customer's registered notification channels (Slack or email). Returns JSON. Each entry's id is the notification-channel registry UUID — pass this value (not channelId) into Fixter alert-rule routing (the channelIds parameter of save_alert_rule / set_alert_rule_delivery, served by a different service). channelId is the Slack-side channel id, included for recognition only. sources lists the notification sources this channel receives — null means all sources, including future ones.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description fully discloses behavior: it returns JSON, explains the semantics of `id`, `channelId`, and `sources` (including null meaning all sources including future ones). It clearly implies a read-only operation and provides essential field-level context without contradictions.

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 two sentences, front-loaded with the main action, then efficiently packs necessary details about field semantics and usage. Every sentence earns its place with no redundancy or fluff.

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?

Given no annotations, no output schema, and zero parameters, the description is self-sufficient. It covers the operation, output structure, field meanings, and how the data integrates with other tools. This is complete for an agent to use the tool correctly without additional information.

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?

There are zero parameters, so the baseline is 4. The description goes beyond by explaining the output fields (`id`, `channelId`, `sources`) and their significance, preempting potential confusion about the data structure, which adds substantial value beyond the empty 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 tool lists the authenticated customer's registered notification channels (Slack or email). It uses a specific verb ('List') and identifies the resource ('registered notification channels'), distinguishing it from sibling tools like add_alert_channel and remove_alert_channel.

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?

While it doesn't explicitly compare to alternatives, it explains how the output `id` should be used in other tools (save_alert_rule/set_alert_rule_delivery) and clarifies the difference between `id` and `channelId`. This provides clear context on when to use the tool and how to apply its results, though it doesn't state when not to use it.

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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