act-within-scope

Resolves reversible execution decisions autonomously while stopping for irreversible or out-of-scope actions.

2|Updated May 14, 2026
One-click install
npx skills add https://github.com/AnthonyPoschen/agent-skills --skill act-within-scope-anthonyposchen
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: act-within-scope
Source: https://github.com/AnthonyPoschen/agent-skills/tree/main/skills/act-within-scope
Command: npx skills add https://github.com/AnthonyPoschen/agent-skills --skill act-within-scope-anthonyposchen

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? AI agents often stall on trivial implementation choices, interrupting users with unnecessary questions, or conversely charge ahead into destructive actions. This Skill defines clear decision boundaries so agents make steady, reversible progress without blocking on the human, while still stopping for genuinely consequential choices. ## Core Features & Use Cases - Decision Triage: Distinguishes ordinary reversible execution choices from decisions involving intent, authority, scope, cost, or external impact that require user input. - Uninterrupted Workflow Completion: Finishes all phases of a sequenced task already in progress instead of pausing after each phase for confirmation. - Hard Safety Boundaries: Always stops for destructive or irreversible actions, security-sensitive changes, production data modifications, irreversible Git operations, and external communications. - Use Case: During a multi-file refactor, the agent chooses reasonable naming and structure from repository conventions, completes the work, and reports decisions and tradeoffs rather than asking about each file. ## Quick Start Ask the agent to complete a coding task end-to-end using the act-within-scope skill, making reasonable reversible decisions on its own and only stopping for irreversible or out-of-scope actions.

Frequently Asked Questions about act-within-scope

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I stop an AI agent from asking too many questions during a task?▼

Apply a decision-boundary policy where the agent resolves ordinary reversible choices from the request, repository evidence, and conventions. It should only ask when intent, authority, scope, cost, or external impact is genuinely uncertain.

When should an AI agent pause and ask the user before proceeding?▼

The agent should stop for destructive or irreversible actions, security-sensitive changes, production data modifications, irreversible Git operations, and sending external communications without explicit authorization. Everything reversible within scope proceeds autonomously.

Should an agent finish all phases of a multi-step workflow without checking in?▼

Yes. Remaining phases of a sequenced workflow already in progress count as ordinary execution, so the agent finishes them rather than stopping after the first phase to ask whether to continue.

What are the limitations of autonomous agent decision-making?▼

Autonomy only covers reversible, in-scope decisions supported by evidence. It must not widen the task beyond the request or disguise product-direction decisions as implementation details, which still require user input.

How does the agent report decisions it made on its own?▼

It states consequential assumptions briefly during work, then reports the decision, outcome, direct proof, and remaining tradeoffs when complete, so the user can review and redirect the result.