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loopgridio
by loopgridio

loopgrid.record_outcome

Record observed downstream outcomes for decisions once execution evidence is available. Attach status, verification source, and optional details to close the decision loop.

Instructions

Record an observed downstream outcome for a decision after execution evidence exists. The integration is responsible for obtaining the outcome from the real downstream system.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
detailsNo
actor_idNoloopgrid-mcp
decision_idYes
verified_againstYes
external_referenceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
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 explains that the integration is responsible for obtaining the outcome, but does not disclose side effects, required permissions, idempotency, error behavior, or what occurs on repeated calls. This is insufficient for a state-changing record operation.

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 concise sentences, front-loaded with the core action and resource, then a key responsibility note. No wasted words or repetition of schema details.

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?

With six parameters, 0% schema description coverage, and no annotations, the description leaves major gaps: status format, required parameter semantics, and tool behavior. The output schema exists but does not compensate for lack of parameter guidance. This is inadequate for correct autonomous invocation.

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. It only implies the meaning of decision_id and verified_against through the phrase 'for a decision after execution evidence exists,' but it gives no details on status values, details structure, actor_id, or external_reference. Parameters remain largely under-explained.

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?

The description clearly states the specific verb 'Record' with a well-defined resource: an 'observed downstream outcome for a decision after execution evidence exists.' It distinguishes this tool from siblings like record_decision, record_review, and record_action by emphasizing downstream outcomes and evidence-based timing.

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

Usage Guidelines4/5

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

The description provides a clear usage condition: use it 'after execution evidence exists' and when the integration has obtained an outcome from the real downstream system. It does not explicitly discuss exclusions or compare to sibling tools, but the timing and responsibility guidance are useful context.

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