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Triage a Batch of JMeter Error Signatures

triage_errors

Map a run's distinct failure signatures to docs.jmeter.ai error playbooks. Error text is sent to classifier.dev for zero-shot classification (public keyless calls are not stored; obvious secrets are redacted first). Prefer signatures shaped as "sampler | response code | response message".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tierNoClassifier tier (default: "fast"). "smart" re-asks only signatures below minConfidence (slower).
errorsYesDistinct error signatures to triage.
minConfidenceNoConfidence threshold for auto-bucketing a signature to a playbook (default: 0.7).
classifierApiKeyNoYour own classifier.dev API key (anonymous quota is shared); never logged.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does so well: it discloses that error text is sent to a third party (classifier.dev), that keyless calls are not stored, that secrets are redacted first, and that 'smart' tier re-asks low-confidence signatures. It stops short of describing rate limits or return shape, keeping it out of the top band.

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 tight sentences, front-loaded with the core action, followed by privacy/transmission context and the input-shape hint. No filler; every sentence earns its place.

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?

There is no output schema, and while the mapping-to-playbooks purpose implies the return, the description doesn't outline what a triage result contains. Given the complexity and the strong privacy/behavioral coverage, it is nearly complete but leaves the output shape to inference.

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 the schema already documents tier, errors, minConfidence, and classifierApiKey. The description's format hint repeats the item-level schema description and adds no new syntax meaning, so the 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 (map) and resource (a run's distinct failure signatures) and the target (docs.jmeter.ai error playbooks). The batch/classifier framing distinguishes it from the singular lookup_error_playbook sibling without needing to open either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives format guidance ("Prefer signatures shaped as 'sampler | response code | response message'") but never states when to use this versus lookup_error_playbook or search_jmeter_docs, nor any exclusion conditions. Usage is implied by the batch-triage framing rather than 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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