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get_investigation_brief

Fetch the full transcript ('brief') of a Fixter investigation that this user is authorized to read. Returns JSON with fields: id, headline, flow, channelId, threadTs, createdAt, sessionEntries. 'sessionEntries' is the raw Claude Agent SDK transcript (tool calls, tool results, assistant messages) from the original investigation. Use to recall context about an investigation that the engineer is currently working on via the Fixter plugin.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
investigationIdYesThe UUID of the investigation to fetch.

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the exact return structure (fields including sessionEntries) and clarifies that sessionEntries is the raw Claude Agent SDK transcript. It also mentions authorization ('authorized to read'), which signals access control. It does not explicitly state side effects, but 'fetch' implies a read-only operation, and the level of detail is adequate.

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 with no fluff. The first sentence states the action and resource; the second provides the return-structure detail and a usage hint. Every sentence earns its place, and key information is front-loaded.

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 simple one-parameter tool with no output schema, the description is complete: it defines action, authorization, return fields, the meaning of the most complex field (sessionEntries), and the intended usage scenario. No additional details seem necessary for correct invocation.

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?

The input schema has 100% description coverage of the single parameter (investigationId is described as 'The UUID of the investigation to fetch'). The tool description adds no further semantics beyond what the schema provides, so the baseline of 3 is appropriate.

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 fetches the full transcript ('brief') of a Fixter investigation, using a specific verb (fetch) and resource (investigation brief/transcript). It distinguishes itself from siblings like list_investigations (which lists) and start_investigation (which creates) by emphasizing the 'full transcript' and the return fields.

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 provides a clear usage context: 'Use to recall context about an investigation that the engineer is currently working on via the Fixter plugin.' It does not explicitly call out alternatives or exclusions, but the intended use case is sufficiently clear for an agent to choose this tool over others.

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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