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List Investigations

list_investigations
Read-onlyIdempotent

List the authenticated customer's recent Fixter investigations (alert-investigation and product-support flows only), newest first. Returns a JSON array of summaries: id, publicSlug, headline, flow, createdAt, and claimedBy (display name of the engineer who claimed it, null when unclaimed). The id feeds get_investigation_brief and start_investigation; the publicSlug feeds start_investigation only. Optional ISO-8601 instant filters 'from'/'to' bound createdAt.

Input Schema

NameRequiredDescriptionDefault
toNoOnly investigations created at or before this ISO-8601 instant.
fromNoOnly investigations created at or after this ISO-8601 instant.
limitNoMax investigations to return (default 20, max 100).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / $schema
      Added value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / limit / format
      Added value: +"int32"
  2. Added

TDQS

A4.2/5.0
Behavior4/5

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

With readOnlyHint, idempotentHint and destructiveHint already declared, the description goes further by describing the return shape (id, publicSlug, headline, flow, createdAt, claimedBy with null semantics) and the filter scope. It does not disclose truncation/pagination behavior — what happens when more than `limit` results exist is unstated.

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?

Three sentences, all load-bearing: scope first, then return shape, then the id/publicSlug routing, then filters. No filler and the most important constraint (newest first, two flows only) is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

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 return-value burden well by enumerating the summary fields and null semantics. The only meaningful omission for a list tool is what happens past the limit (truncation vs. cursor), which leaves the agent guessing about completeness of results.

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?

Schema description coverage is 100%, so 'from'/'to' and 'limit' are already documented, including default 20 and max 100. The description's note that from/to bound createdAt largely repeats the schema wording, adding no new syntax or semantics; 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?

States a specific verb (List), the exact resource (the authenticated customer's Fixter investigations), narrows scope to two flows, and specifies ordering (newest first). An agent can tell what it retrieves without opening the schema.

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?

It gives clear downstream context — the returned id feeds get_investigation_brief and start_investigation, and publicSlug feeds start_investigation only — which effectively tells the agent when to reach for this tool. It stops short of naming a competing alternative (e.g. list_issues) or an explicit when-not-to-use condition.

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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