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aipm-engine

AI Process Manager

by aipm-engine

report_action_outcome

Report UI action outcomes and failure reasons to build per-app recipes, preventing future agents from repeating dead ends.

Instructions

Report one UI action outcome (invoke/set_value/focus). Feeds per-app recipes in get_app_knowledge. Metadata only — never screen content or typed text. Report FAILURES too (ok=false plus reason): they become common_failures and stop the next agent from repeating the same dead end.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
msNoAction duration in ms
okNoAction succeeded?
appYesApp where action occurred
actionYesAction performed (invoke, set_value, focus)
reasonNoOnly when ok=false. Closed vocabulary: elemento_nao_encontrado, elemento_nao_suporta_invoke, elemento_nao_suporta_set_value, campo_somente_leitura, janela_nao_encontrada, ui_timeout, acao_bloqueada, erro_uia, outro. Anything else is stored as "outro" — free text never reaches disk.
element_nameNoElement name (e.g. "Save")
element_roleNoElement role (Button, Edit, ...)
Behavior4/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, but the description adds meaningful behavior: 'Metadata only — never screen content or typed text' clarifies privacy constraints. It also discloses that failures become common_failures for future agents. This goes beyond the annotations without contradicting them.

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?

The description is three sentences long, front-loaded with the core purpose, and every sentence adds distinct value: what it does, how it feeds into recipes, and the importance of reporting failures. No filler or redundancy.

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?

For a telemetry tool with 7 parameters and no output schema, the description covers the essential aspects: purpose, timing, and data sensitivity. It lacks details about return values or potential side effects, but these are less critical for a reporting tool. The schema and annotations fill remaining gaps.

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 100%, so parameters are individually described in the schema. The main description adds context about the purpose of ok=false and reason (e.g., 'they become common_failures'), which enriches understanding. However, it does not provide per-parameter details beyond what the schema already offers, so it stays at the baseline.

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 'Report one UI action outcome (invoke/set_value/focus)', which is a specific verb and resource. It also mentions 'Feeds per-app recipes in get_app_knowledge', distinguishing it from sibling tools like report_task_outcome. The purpose is unambiguous and well-scoped.

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 implies when to use it: after a UI action, report its outcome. It explicitly instructs to 'Report FAILURES too (ok=false plus reason)', giving concrete usage guidance. However, it does not explicitly contrast with report_task_outcome or name alternatives, so the guidance is not fully 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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