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aipm-engine

AI Process Manager

by aipm-engine

report_task_outcome

Reports task completion metadata to local telemetry at the end of a computer-use task. Enables AI Process Manager to track app knowledge and economic stats without screen content.

Instructions

Report task outcome to local telemetry (metadata only — never screen content). Call at END of a computer-use task. Feeds get_app_knowledge and get_economy_stats.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
appYesPrimary app (e.g. chrome.exe)
taskNoShort task description (metadata)
notesNoShort notes (metadata)
stepsNoNumber of steps/actions
successNoTask succeeded?
duration_sNoDuration in seconds
tokens_estimatedNoEstimated tokens consumed
screenshots_avoidedNoScreenshots avoided via structured state
Behavior4/5

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

Annotations are minimal (readOnlyHint: false, destructiveHint: false). The description adds crucial behavioral context beyond them: it emphasizes 'metadata only — never screen content', which is a privacy guarantee, and says it feeds other tools. This meaningfully supplements the sparse annotations without contradiction.

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?

Three short sentences, each earning its place: the core action, the usage timing, and the downstream effects. It is front-loaded with the main purpose and contains no filler.

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 an 8-parameter tool with no output schema, the description is fairly complete: it explains the purpose, when to call, and important safety constraints. It does not describe return values or error behavior, but these are likely minor for a telemetry reporting tool and are well-covered by the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so parameters are already fully described. The description adds a global semantic constraint that all fields are metadata and forbids screen content, which is not present in the schema. This extra layer helps avoid misuse, though it does not detail individual parameters beyond the schema.

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?

Description clearly states the verb ('Report'), the resource ('task outcome'), and the destination ('local telemetry'). It also distinguishes from the sibling report_action_outcome by specifying 'at END of a computer-use task', making the scope unique.

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?

Provides explicit timing ('Call at END of a computer-use task') and mentions downstream consumers (get_app_knowledge, get_economy_stats) to help decide when to use. However, it does not explicitly name alternative tools or mention when not to use, leaving room for clearer exclusion guidance.

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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