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apply_production_operation

Destructive

Plan or execute one proposed production operation using its original plan and confirmation token. Requires unchanged task state, prior receipts; returns bounded results and postconditions.

Instructions

Plan one proposed operation through its original tool, or execute using that exact plan's confirmation. Requires unchanged task state; later operations require the preceding applied receipt. Returns bounded result references and observed postconditions, not an audible judgment.

Input Schema

NameRequiredDescriptionDefault
dryRunNo
taskIdYesArtifact ID returned by a producer tool.
planHashNoOriginal tool's plan hash.
projectIdYesPrivate project namespace.
operationIndexYes
confirmationTokenNoOriginal tool's single-use confirmation token.
previousReceiptIdNoArtifact ID returned by a producer tool.
expectedStateVersionYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.3.1
    • removedOutput schema / additionalProperties
      Removed value: -true
    • addedOutput schema / anyOf
      Added value: +[
      +  {
      +    "properties": {
      +      "checkSource": {
      +        "enum": [
      +          "caller",
      +          "specialist"
      +        ]
      +      },
      +      "operationIndex": {
      +        "minimum": 0,
      +        "type": "integer"
      +      },
      +      "status": {
      +        "enum": [
      +          "planned",
      +          "applied",
      +          "rejected",
      +          "outcome_unknown",
      +          "postconditions_failed",
      +          "pending_postconditions",
      +          "pending_user_action"
      +        ]
      +      },
      +      "taskId": {
      +        "pattern": "^[a-f0-9]{64}$",
      +        "type": "string"
      +      }
      +    },
      +    "required": [
      +      "taskId",
      +      "operationIndex",
      +      "status",
      +      "checkSource"
      +    ],
      +    "type": "object"
      +  },
      +  {
      +    "properties": {
      +      "error": {
      +        "properties": {
      +          "message": {
      +            "type": "string"
      +          },
      +          "outcome": {
      +            "enum": [
      +              "unknown",
      +              "not_executed"
      +            ]
      +          }
      +        },
      +        "required": [
      +          "message",
      +          "outcome"
      +        ],
      +        "type": "object"
      +      }
      +    },
      +    "required": [
      +      "error"
      +    ],
      +    "type": "object"
      +  }
      +]
  2. Addedv0.3.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare destructive=true, idempotent=false and openWorld=true. Beyond that, the description adds real behavioral context: the strict unchanged-task-state requirement, sequential receipt dependency, and the fact that it returns bounded result references and observed postconditions rather than a verdict. It stops short of stating what state is mutated or what the destructive effect is.

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?

Three dense but front-loaded sentences with no filler; the plan/execute distinction leads. It is efficient, though the phrasing is abstract enough that some sentences require re-reading.

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?

An output schema exists, so return values need not be spelled out (the description still flags bounded references and postconditions). For a high-complexity, 8-parameter, destructive, two-phase tool, the prerequisites and sequencing are covered adequately, leaving only per-parameter detail to the schema.

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 63% across 8 parameters. The description usefully implies the dryRun-confirmationToken relationship ('plan... or execute using that exact plan's confirmation') and the expectedStateVersion/operationIndex semantics through 'unchanged task state' and 'later operations'. But planHash and previousReceiptId semantics are left entirely to the schema, so it only partially compensates for the coverage gap.

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 two-mode verb+resource: plan a proposed operation via its original tool, or execute using that plan's confirmation. An agent can grasp that this is a plan/execute gate for a single production operation, though 'one proposed operation' stays abstract and no sibling (e.g. run_production_task) is named for disambiguation.

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?

It provides ordering/prerequisite guidance ('requires unchanged task state; later operations require the preceding applied receipt'), which implies when the tool can be invoked. However, it never names an alternative tool or states when NOT to use this versus the sibling production/lifecycle tools, so usage context is implied rather than explicit.

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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