Incident Library

Get a root cause, component, symptom, contributing factor or organisation

get_topic

Read-onlyIdempotent

Returns one vocabulary value with every case that carries it and, under related, the other four kinds counted over those cases with case ids: for a symptom, the root causes behind it (answers 'what usually causes this'); for a root cause, the components and factors seen with it. Use when you already have a slug and want the picture around it; use vocab to find the slug from words, list_incidents for a plain paged list, search_incidents for a symptom sentence. kind is the slug's category: root_causes, components, symptoms, factors or orgs (the organisations that published cases). With symptoms, the page keeps only the cases that sentence finds, best match first, and query echoes it, so 'certificate expiry, but only where DNS was involved' is one call. The answer is not paged: count and cases hold every case of the value (at most a few dozen today). An unknown slug or a slug of the wrong kind returns an error result naming it; nothing is written.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "kind": "<kind>",
      "slug": "<slug>"
    },
    "name": "get_topic"
  }
}

Input Schema

Name	Required	Description
`kind`	Yes	Which category the slug belongs to
`slug`	Yes	The value's slug, e.g. capacity, coredns, pod-pending, no-alerting, github
`symptoms`	No	A symptom sentence that restricts the page to the cases it finds

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 11, 2026
- addedInput schema / properties / kind / description
```
Added value: +"Which category the slug belongs to"
```
First observedNov 10, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Beyond the readOnly/idempotent annotations, it discloses that results are not paged (count and cases hold every case, at most a few dozen), that symptom filtering is best-match-first, that `query` echoes the sentence, and that an unknown or wrong-kind slug returns an error naming it with nothing written. These are behavioral facts an agent cannot get from the annotations or schema.

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 return shape, then routing, then parameter semantics, then error behavior — a sensible order with no filler sentences. It is dense and parenthesis-heavy, and the phrase '`query` echoes it' is slightly ambiguous since `query` is not an input parameter, which costs a point.

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?

With no output schema, the description carries the burden of describing returns and does so: `count`, `cases`, and `related` with case ids and per-kind counts. For a three-parameter read tool it also covers unpaged sizing, error behavior, and side-effect freedom, leaving nothing an agent needs before calling.

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 coverage is 100%, so the schema already documents all three parameters; the description still adds meaning by spelling out what `kind`'s enum values represent (including 'orgs = the organisations that published cases') and by clarifying that `symptoms` restricts the page rather than acting as a general text search. That is real added value above the schema, though it stops short of per-parameter edge cases such as slug format expectations beyond the example.

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?

States a specific verb and resource: returns one vocabulary value plus every case carrying it, with `related` holding the other four kinds counted over those cases. It also differentiates itself from siblings by naming vocab, list_incidents, and search_incidents and describing what each does instead.

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?

Explicit routing guidance: 'Use when you already have a slug and want the picture around it' versus 'use vocab to find the slug from words, list_incidents for a plain paged list, search_incidents for a symptom sentence.' It also gives a concrete combined-use example ('certificate expiry, but only where DNS was involved' is one call), which tells the agent when the `symptoms` filter is the right move.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Incident Library tools Inspect

Try in Browser

Claude Code, inside the Godot 4 editorFlockbay puts an AI agent in the real Godot 4 editor: it writes GDScript, runs your game and fixes what breaks. Free, or bring your own Claude Code or Codex.flockbay.comAd

Glama MCP Gateway

Add one secure layer between your agents and this server.