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Glama

vaara_report_outcome

Report the observed severity of an executed action using its action_id to close the feedback loop, so risk scoring improves with real outcomes.

Instructions

Report what happened after an action was executed. This closes the feedback loop — the scorer learns from outcomes to improve future risk assessments. Provide the action_id from vaara_intercept and the observed severity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
action_idYesThe action_id returned by vaara_intercept
descriptionNoHuman-readable description of what happened
outcome_severityYesHow severe was the outcome? 0.0 = completely safe, 1.0 = catastrophic

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.14.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It does disclose a genuine non-obvious trait — that the reported outcome feeds a scorer that improves future risk assessments — but says nothing about auth requirements, whether reporting is mandatory or idempotent, or what happens on an unknown action_id.

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?

Short, front-loaded with the action, and the rationale sentence earns its place by explaining the feedback loop. The final instruction sentence is mildly redundant with the schema's parameter descriptions.

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

Completeness3/5

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

All three parameters are documented via the schema, but with no annotations and no output schema the description should ideally state what a successful report returns or what happens if the action_id is unknown. It covers the why but not the mechanics.

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 the schema already documents action_id, outcome_severity (with its 0.0–1.0 scale) and description. The prose mostly restates the schema's own hints rather than adding format or edge-case guidance, 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 — reporting the observed outcome of an executed action — and ties itself to vaara_intercept as the source of the action_id. It does not explicitly differentiate itself from vaara_verify_receipt, so an agent must infer the boundary between 'report outcome' and 'verify receipt'.

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 timing is explicit ('after an action was executed') and the data provenance is stated ('the action_id from vaara_intercept'), which gives clear context for when to call it. It stops short of naming when not to use it or contrasting it with vaara_verify_receipt/vaara_check.

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