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record_execution_receipt

Record execution costs and outcomes for a slice, including verification, repair, and human costs, to capture durable spend and enable cost-aware AI execution.

Instructions

Record model/agent cost and outcome for a slice; durable cost includes verification, repair and human cost.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outcomeNoUNKNOWN
actor_idYes
currencyNoEUR
metadataNo
model_idNo
slice_idYes
family_idYes
human_costNo
work_classNoUNCLASSIFIED
repair_costNo
input_tokensNo
output_tokensNo
execution_costNo
verification_costNo
context_tokens_rawNo
context_tokens_compiledNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It discloses that the record is 'durable' and includes verification, repair, and human cost, which is useful, but it does not state whether this is an insert-only operation, whether it overwrites existing receipts, whether it requires prior slice state, or what the response contains. For a write operation with no annotation coverage, this is a significant gap.

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 a single sentence with no filler, and the core action is front-loaded. It is concise, though it could add a bit more guidance without becoming bloated.

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?

Given 16 parameters, 0% schema description coverage, no annotations, and a write operation, the description is not complete enough. It does not explain the required identifiers, the outcome/work_class vocabulary, the token fields, or the behavior of the durable cost aggregation. The output schema exists but the input semantics are largely unexplained.

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 compensate, but it only explains the cost-related fields at a high level ('verification, repair and human cost'). It does not explain the meaning of family_id, slice_id, actor_id, outcome, work_class, model_id, currency, token fields, or metadata. With 16 parameters and zero schema descriptions, this is a major 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 verb ('Record') and resource ('model/agent cost and outcome for a slice'), and clarifies that the durable cost includes verification, repair, and human cost. It is clear enough to distinguish it from siblings like model_stats or update_slice_progress, though it doesn't explicitly name a sibling alternative.

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 description implies this tool is used after a slice execution to record costs and outcome, but it does not explicitly state when to use it versus alternatives like update_slice_progress or claim_done. There is no when-not-to-use guidance or mention of prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.