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List Flows

list_flows
Read-onlyIdempotent

List the caller's flows: every request route or scheduled job that opened a trace in the last 21 days, with what its callers got. A flow is a service and a route or job name. Each row reports calls in the last 24 hours, callers hit in the last 7 days (calls that failed while carrying an exception or a 5xx), exceptions linked by trace and its top three issues with the status the caller got, as a code such as 401 or 500, or silent. Rows come worst first. To answer which routes are hurting callers, call this and read callersHit7d on each row; to see every issue behind one route, call get_flow with that row's id.

Input Schema

NameRequiredDescriptionDefault
limitNoMost flows to answer, from 1 to 200 (default 50)
queryNoFree-text match on the flow's service or its route or job name
environmentNoOnly count what happened in this deployment environment, such as production (default every environment)
includeLeavesNoAlso list the leaf calls that the service makes on behalf of a flow, such as outgoing HTTP calls and queries (default false)

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
  3. Removed
  4. Added
  5. Removed
  6. Added
  7. Removed
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  10. Added

TDQS

A4.4/5.0
Behavior4/5

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

With readOnlyHint/idempotentHint already covering safety, the description adds real substance: the 21-day window, what each row aggregates (24h calls, 7d caller hits), the definition of a caller hit (failed while carrying exception or 5xx), and row ordering (worst first). Return-shape detail is strong for a tool with no output schema; it stops short of one or two edges but is well above the annotation bar.

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 core definition, then row contents, then routing advice. Some middle sentences are dense and run long, but every sentence carries information (window, aggregation, ordering, alternative). Only mild tightening would be possible.

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 read-only list tool with no output schema, the description is complete: it defines the entity, the window, the per-row metrics, the ordering, and the follow-up call. An agent can decide to call it, know what comes back at a conceptual level, and know where to go next.

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 coverage is 100% and each parameter has its own description, so the schema already supplies semantics. The description adds the default window framing (last 21 days, last 24 hours) but doesn't explain includeLeaves or environment interactions beyond what the schema says. Baseline 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?

States a specific verb (List) and resource (flows), then defines 'flow' concretely as 'a service and a route or job name' and scopes the time window (last 21 days). An agent can distinguish this from get_flow and from generic list_* siblings without opening any schema.

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?

Gives an explicit use case ('which routes are hurting callers... read callersHit7d') and routes to the alternative ('to see every issue behind one route, call get_flow with that row's id'). When-to-use and when-to-use-something-else are both stated.

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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