본문으로 건너뛰기
cccskills
무료GitHub에 공개

ai-loop

Guide a scoped coding task through specification, implementation, and review. Set acceptance criteria, verification checks, iteration limits, and approval gates, then correct identified gaps until the requirements pass or a stopping condition is reached.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.

설치 방법 보기

이럴 때 유용합니다

  • Build a small feature from specification through verification
  • Modify a module against explicit acceptance criteria
  • Repeat fixes and checks within an iteration limit
  • Define approval gates for risky development actions

포함된 파일(1)

  • SKILL.md7.8 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

AI-Loop Skill

Overview

The ai-loop skill structures a bounded development cycle for agentic workflows. By dividing the process into distinct planning (Spec), implementation (Build), and validation (Review) phases, it helps an agent build and correct scoped code changes while keeping requirements, risk gates, and stop conditions explicit.

When to Use This Skill

  • Use when you need a feature built from scratch or heavily modified, and you want the agent to handle the lifecycle (specification, implementation, and verification) inside one clearly bounded workflow.
  • Use when working with isolated components, modules, or features that have well-defined scopes and constraints.
  • Use when the user asks for a complete development pass but the work still has clear success criteria, a reasonable verification path, and no unresolved safety or product decisions.

How It Works

This skill executes a controlled development loop composed of three phases: Spec, Build, and Review. When invoked, the agent moves through those phases until the scoped requirements pass verification, a stop condition is reached, or human approval is needed.

Before starting, define:

  • The maximum number of build-review iterations.
  • The verification commands or manual checks that count as evidence.
  • The actions that require explicit approval, such as destructive commands, production changes, external service writes, or broad architectural pivots.

Phase 1: Spec (Planning)

  1. Reuse the current request, accepted plan and existing artifacts. Ask only for essential missing scope or acceptance criteria; do not repeat answered questions.
  2. Do not start building yet.
  3. When you have enough information, use the existing specification or, when needed, save a scoped new one at specs/<feature-name>.md without overwriting user work.
  4. The spec must include:
    • The objective
    • The exact requirements
    • Edge cases to handle
    • A concrete definition of done that someone could check the build against
    • The iteration budget, verification commands, and approval gates.

Phase 2: Build (Implementation)

  1. Read the spec you just created in specs/<feature-name>.md.
  2. Build exactly what it describes.
  3. Do not add features, do not refactor unrelated code, and do not invent requirements that aren't in the spec.
  4. Focus strictly on fulfilling the spec. List which spec requirements you covered so the review step can check them.

Phase 3: Review (Verification)

  1. Compare your implementation against specs/<feature-name>.md.
  2. Go requirement by requirement and verify if it was met. List every gap, bug, or missing piece, naming the exact spec item each one fails.
  3. If anything fails and the iteration budget is not exhausted, write the specific fixes needed and loop back to Phase 2 (Build) to address them.
  4. Use the agreed iteration/resource limits and scope. Ask for material product or consequential authorization decisions that are not already resolved; routine repairs within the accepted outcome need no new checkpoint. Continue independent work when a dependent check is unavailable.
  5. Only pass the build and conclude the skill execution when every requirement in the spec is fully met and the declared verification evidence has passed.

Examples

Example 1: Creating a Basic Statistics Helper

User:

I want to add a utility for calculating basic statistics (mean, median, mode) of an array of numbers.

Agent (Phase 1 - Spec):

I can help with that. To get started, what programming language should this statistics calculator be implemented in? Also, how should empty arrays or invalid inputs be handled?

User:

JavaScript. If the array is empty, return null. If there are non-numbers, ignore them.

Agent (Phase 1 - Spec):

Thank you. I have created the specification file at specs/stats-calculator.md with the requirements we discussed. Now, I will start implementing it.

Agent (Phase 2 - Build):

(Creates stats_calculator.js and implements mean, median, and mode matching the spec exactly) I have finished implementing the calculator. I will now verify the implementation.

Agent (Phase 3 - Review):

Checking implementation against specs/stats-calculator.md:

  • Requirement: mean calculation -> PASS
  • Requirement: median calculation -> PASS
  • Requirement: mode calculation -> PASS
  • Requirement: empty array returns null -> PASS
  • Requirement: non-numbers are ignored -> FAIL (I noticed mode doesn't filter out non-numbers).

I will now loop back to Phase 2 to fix the mode function.

Agent (Phase 2 - Build Loop-Back):

(Fixes mode to filter out non-numbers) I have updated the implementation. Let's re-verify.

Agent (Phase 3 - Review):

  • Requirement: mode filters non-numbers -> PASS

All requirements passed! The statistics calculator is complete and verified.

Best Practices

  • ✅ Do ask clarifying questions one at a time to avoid overwhelming the user during the planning phase.
  • ✅ Do document edge cases explicitly in specs/<feature-name>.md before writing any code.
  • ✅ Do stick strictly to the approved specification during the build phase.
  • ✅ Do cap the loop with a small iteration budget and report exactly what remains if the budget is exhausted.
  • ✅ Do pause for explicit approval before destructive, production, credentialed, or externally visible actions.
  • ❌ Don't implement extra features or perform unrelated refactorings that aren't specified.
  • ❌ Don't skip the review phase or pass it without verifying every single requirement.
  • ❌ Don't keep retrying the same failing fix without new evidence or a changed approach.

Limitations

  • This skill requires sufficient context about the feature to be provided during the Spec phase.
  • It is best suited for isolated features or tasks with clear boundaries, rather than open-ended architectural refactoring.
  • The review phase relies on the agent's self-assessment against the generated spec; manual review is still recommended for critical systems.
  • It is not a replacement for human approval on security-sensitive, destructive, production, compliance, or externally visible changes.
  • Report conflicting requirements or unavailable verification accurately and continue useful independent work; do not mark missing tests as passed or request credentials in chat.

Security & Safety Notes

  • Be cautious when running or testing code generated during the Build phase. Always run tests in a safe, sandboxed environment.
  • Avoid executing arbitrary shell commands provided directly by the user without validating their safety.
  • Make sure no hardcoded secrets, keys, or credentials are added to the code or specifications.
  • Treat production deploys, data migrations, payment flows, credential changes, and external write actions as approval-gated work.

Common Pitfalls

  • Problem: The agent tries to build a huge system all at once, leading to an overcomplicated spec and incomplete implementation. Solution: Keep the scope of ai-loop to small, modular features. Break larger systems into multiple independent loops.
  • Problem: The spec is vague, causing the build phase to rely on assumptions. Solution: Spend extra time in the planning phase asking targeted questions to pin down requirements.

Related Skills

  • @plan-writing - For writing more detailed implementation plans for larger projects.
  • @ask-questions-if-underspecified - For standard guidelines on interviewing the user.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Assess a new or existing AI project by examining its code, goals, and constraints. Recommend skills confirmed to exist in the available registry, then outline tasks and implementation phases with dependencies, completion criteria, and checks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Planning the first steps of a new AI project
  • Assessing technical issues in an existing project
  • Selecting relevant skills from an available registry
sickn33/agentic-awesome-skills4.8만2026년 10월 19일 업데이트

007

무료

Review code and infrastructure for security risks, map potential threats, and plan stronger defenses. The skill covers OWASP checks, attack and defense exercises, and incident response, with validation required for each environment.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Reviewing code and infrastructure security
  • Mapping threats with STRIDE or PASTA
  • Planning stronger security settings
sickn33/agentic-awesome-skills4.8만2026년 10월 19일 업데이트

Turn a repeatable task into an Andru.ia skill with clear inputs, outputs, examples, and limits. Draft SKILL.md, check the folder structure and required validations, and prepare a pull request describing the changes for review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Creating a skill for a repeatable task
  • Improving an existing skill’s examples and limits
  • Validating skill files and preparing a pull request
sickn33/agentic-awesome-skills4.8만2026년 10월 19일 업데이트

Prepare an industry briefing once a project's sector is defined. It covers sector context, potentially applicable regulations, familiar interface patterns, technology choices, and risks, while separating verified evidence from hypotheses and questions requiring further review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Researching industry requirements before product design
  • Checking regulations for a project's jurisdiction
  • Choosing interface patterns familiar to target users
sickn33/agentic-awesome-skills4.8만2026년 10월 19일 업데이트

Create presentation drafts from text, outlines, or documents through the 2slides API. Match a reference image's style, choose themes, add AI voice narration, and export slide images or audio for review and use.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Create a presentation from text or an outline
  • Summarize a document into slides
  • Match slide styling to a reference image
sickn33/agentic-awesome-skills4.8만2026년 10월 19일 업데이트

Plan a 360-degree or peer feedback process and create empty response templates from confirmed requirements. Produces consistent CSV, SQL, JSON Schema, or Notion property mappings while keeping visibility choices and scoring configuration separate.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Plan an anonymous peer feedback process
  • Create a CSV template for feedback responses
  • Align feedback fields across SQL and JSON Schema
sickn33/agentic-awesome-skills4.8만2026년 10월 19일 업데이트

sickn33의 스킬 모두 보기

이 스킬의 문제 신고