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Flow Run Status

lab_flow_status
Read-only

Use when the person asks how far a flow/pipeline run is, whether it finished, why it stopped or hangs, or what a step returned. State of a Flow (Pipeline) run started with lab_flow_starten: the run's status (wartet, laeuft, fertig, fehlgeschlagen, abgebrochen) and, per node, its status, attempts, result and error. A node's result is exactly what its tool returned — ids from there go into the next tools. fehler is the run's stored message as written by the executor; when fehler_text is present it is the same message in the person's language — quote that one to the person. With angebot_id instead of lauf_id it finds the run started from that offer — gefunden: false means no run was created from it, so nothing was charged for it.

Input Schema

NameRequiredDescriptionDefault
lauf_idNoFrom lab_flow_starten
angebot_idNoFrom lab_flow_angebot — finds the run started from this offer (when lab_flow_starten's answer was lost)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  2. Changed2 schema fields changed
    • addedInput schema / properties / angebot_id
      Added value: +{
      +  "description": "From lab_flow_angebot — finds the run started from this offer (when lab_flow_starten's answer was lost)",
      +  "minLength": 1,
      +  "type": "string"
      +}
    • removedInput schema / required
      Removed value: -[
      -  "lauf_id"
      -]
  3. Added

TDQS

A4.6/5.0
Behavior5/5

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

readOnlyHint=true is consistent, and the description goes well beyond it: it enumerates the five status values, describes per-node attempts/result/error, explains that `fehler` is the executor's stored message while `fehler_text` is the localized version to quote, and defines `gefunden: false` as 'no run was created from this offer, so nothing was charged'. With no output schema, this is the only place that behavior could be disclosed.

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 a 'Use when...' trigger sentence, then the return shape, then two edge-case notes. Dense and largely earning its place, though the localized-error and billing implications are packed into a single long final sentence that could be split for scanability.

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?

No output schema exists, so the description must carry the return-value burden, and it does: status vocabulary, per-node fields, error message duality, and the not-found case. Combined with 100% parameter coverage and a declared read-only annotation, an agent has everything needed to call and interpret this tool.

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 baseline is 3, but the description adds real semantics the schema lacks: lauf_id vs angebot_id are mutually alternative lookups, and the angebot_id branch is described as the recovery path when the start response was lost. It does not state what happens if both are supplied, which keeps it below 5.

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?

Names a specific verb and resource ('State of a Flow (Pipeline) run started with lab_flow_starten') and enumerates exactly what comes back: run status values plus per-node status, attempts, result and error. It is clearly separable from siblings like lab_flow_starten, lab_flow_fortsetzen, lab_batch_status and lab_job_status because it scopes itself to a flow run.

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?

Openers give explicit trigger conditions: the person asks how far a run is, whether it finished, why it stopped or hangs, or what a step returned. It also explains the angebot_id path for when lab_flow_starten's answer was lost. It never explicitly excludes alternatives (e.g. lab_batch_status or lab_job_status), so it stops short of a full when/when-not routing rule.

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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