RQM WaveEngine Jobs

Optimize Processing Pipeline

wave_optimize_processing_pipeline_v1

Idempotent

Problem: Optimize this supported Wave pipeline against the supplied operation-count objective and equivalence rule. Input: JSON with operations, fixture, objective, maximum operations, maximum equivalence.... Result: candidate pipeline and equivalence checks. Limits: Bounded signal processing only; 8 channels; 4096 samples/channel.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "schema_version": "<schema_version>",
      "request": "<request>",
      "idempotency_key": "<idempotency_key>",
      "max_total_price": "<max_total_price>"
    },
    "name": "wave_optimize_processing_pipeline_v1"
  }
}

Input Schema

Name	Required	Description	Default
`request`	Yes
`schema_version`	Yes
`idempotency_key`	Yes
`max_total_price`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 25, 2026

changedOutput schema / anyOf

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+      "job_id",
+      "status",
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+          "FEATURE_DISABLED",
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+          "QUOTE_IDEMPOTENCY_CONFLICT",
+          "QUOTE_NOT_AVAILABLE",
+          "QUOTE_REQUEST_INVALID",
+          "QUOTE_MISMATCH",
+          "PRICE_LIMIT_EXCEEDED",
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+          "ARTIFACT_PREFERENCE_UNAVAILABLE",
+          "INSUFFICIENT_BALANCE",
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+          "PRODUCT_REJECTED",
+          "PRODUCT_UNAVAILABLE",
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First observedSep 12, 2026

TDQS

B3.1/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is partly covered. The description adds useful domain constraints (bounded signal processing, 8 channels, 4096 samples/channel) and a result summary, but omits important operational behavior such as job submission semantics, pricing via max_total_price, and idempotency-key usage.

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?

The description is front-loaded and organized into Problem, Input, Result, and Limits sections, which makes it easy to scan. It is somewhat marred by trailing ellipses and 'maximum equivalence....' but remains efficient overall.

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

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a complex tool with a nested request object, 0% schema description coverage, and job-submission parameters including a fixed max_total_price. The description covers the optimization objective and domain limits but omits critical operational context about the job lifecycle, pricing, idempotency, and how the required top-level fields should be populated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry the burden. It names nested request fields like operations, fixture, objective, maximum operations, and maximum equivalence, but does not explain the required top-level parameters schema_version, idempotency_key, and max_total_price, nor their formats or significance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: optimize a Wave processing pipeline against an operation-count objective and equivalence rule, returning a candidate pipeline and equivalence checks. It does not explicitly distinguish itself from nearby siblings such as wave_verify_wave_pipeline_v1 or wave_compile_curated_processing_recipe_v1, but the optimization objective makes the intent reasonably clear.

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?

Usage is implied by the 'Problem' framing: use this when optimizing a supported Wave pipeline against an operation-count objective. However, there is no explicit when-to-use guidance, no exclusions, and no routing to alternatives such as verification or recipe compilation tools.

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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