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ProteinIQ

by io.proteiniq
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Submit ProteinIQ Job

submit_job

Submit an asynchronous ProteinIQ job. Use get_job or get_result with the returned job ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesHuman-readable job name.
toolYesProteinIQ tool ID.
inputYesPublic API job input payload. Use the tool contract from get_tool.
billingNoOptional spending limit for a minute-billed job. The job otherwise uses credits as it runs.
settingsNoTool settings keyed by setting ID.
project_idNoOptional workspace project ID.
idempotency_keyNoOptional idempotency key for safe retries.
max_quoted_creditsNoMaximum fixed charge or initial runtime reservation accepted for this submission.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / billing / $schema
      Added value: +"https://json-schema.org/draft/2020-12/schema"
    • changedInput schema / properties / billing / additionalProperties
      Previous value: -trueNew value: +false
    • addedInput schema / properties / billing / properties
      Added value: +{
+  "maxReservedCredits": {
+    "exclusiveMinimum": 0,
+    "maximum": 9007199254740991,
+    "type": "integer"
+  },
+  "max_reserved_credits": {
+    "exclusiveMinimum": 0,
+    "maximum": 9007199254740991,
+    "type": "integer"
+  }
+}
  2. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare the write-but-not-destructive safety profile, and the description adds the key trait that execution is asynchronous and that a job ID is returned for polling. It omits the credit/billing consumption behavior that the schema's billing and max_quoted_credits params imply, which is relevant for a submission that spends resources.

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?

Two tight sentences with zero filler; the core action is front-loaded and the follow-up guidance follows immediately. Every clause earns its place.

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?

For an 8-parameter, deeply nested job-submission tool with no output schema, the description is thin: it does not explain the tool/input contract, the cost/credit implications, or how it relates to quote_job and submit_batch. It covers the return flow but little else an agent needs to submit correctly.

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 every parameter (tool, name, input, billing, settings, project_id, idempotency_key, max_quoted_credits) is already documented in the schema. The description adds no parameter-level meaning, so the baseline 3 applies.

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?

States a specific verb and resource ('Submit an asynchronous ProteinIQ job') and names the follow-up tools, so the agent knows this creates a job. However it never distinguishes itself from the close sibling submit_batch, nor from quote_job which precedes submission.

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?

The 'asynchronous' framing implies the usage context (long-running work you poll later), and it names get_job/get_result as follow-ups. But there is no explicit when-to-use vs submit_batch or quote_job, and no stated prerequisites or exclusions.

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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