Structure bounded dev cycles with plan-build-review phases
AI-Loop structures scoped development into specification, implementation, and requirement-by-requirement review with iteration limits and stop gates.
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Why it matters
Orchestrate agentic code development through explicit planning, implementation, and validation phases with built-in risk gates and stop conditions to ensure scoped, correctable changes.
Outcomes
What it gets done
Define requirements and constraints in a structured Spec phase
Generate code implementations during the Build phase
Validate outputs against requirements in the Review phase
Loop through phases until stop conditions are met or risks trigger exit
Install
Add it to your toolbox
Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-ai-loop | bash After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.
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Overview
A bounded development workflow with separate specification, build, and review phases. It tracks requirement coverage, verification evidence, iteration limits, and decisions that need human input. Use it for an isolated feature or module with clear success criteria and a practical verification path.
What it does
AI-Loop organizes development into a bounded Spec, Build, and Review cycle. It helps define a feature, implement the agreed requirements, compare the result against the specification, and correct identified gaps within an explicit iteration budget. The loop ends when every requirement passes the declared verification, a stop condition is reached, or a decision needs human input. Scope, evidence, and approval boundaries are established before implementation begins.
The Spec phase asks one focused question at a time to establish the goal, must-have requirements, constraints, and definition of done. It does not start building while those decisions are unresolved. The resulting specification is saved as a feature-named Markdown file in the specs directory and includes the objective, exact requirements, edge cases, checkable completion criteria, maximum build-review iterations, verification commands or manual checks, and approval gates.
The Build phase reads that document and implements exactly what it describes. It records which requirements were covered so the review can compare work with the same contract. Additional features, unrelated refactoring, and invented requirements are outside the loop's scope. Review then checks each requirement individually, naming gaps, bugs, or missing pieces by the exact specification item they fail.
When to use - and when NOT to
Use this skill for a new or substantially modified feature, component, or module with clear boundaries and a reasonable verification path. It fits a complete development pass when success criteria are concrete and no unresolved product or safety decisions prevent execution. Large systems should be broken into smaller independent loops rather than handled as one oversized specification.
It is less suited to open-ended architectural refactoring or work with insufficient context. Conflicting requirements, tests that cannot run, unavailable credentials or systems, or exhausted iteration limits are reasons to stop and report the exact remaining issue. The review is the agent's assessment against its generated specification; critical systems still warrant manual review. This workflow does not replace human approval for sensitive, destructive, production, compliance, or externally visible changes.
Inputs and outputs
Inputs are the desired feature, language and behavior constraints, edge-case decisions, success criteria, verification environment, and a small iteration budget. The specification becomes the durable reference for both implementation and review. Outputs include the specification file, scoped code changes, a requirement coverage list, and the evidence and findings from verification.
A statistics-helper specification might require mean, median, and mode, return null for empty arrays, and ignore non-numbers. Review detects that mode failed the non-number requirement, sends that specific fix back to Build, and verifies it again. This illustrates repairing an identified requirement gap rather than repeatedly trying the same unsuccessful change without new evidence.
A failed check returns to Build only while the budget remains and the fix stays within the agreed specification. Changes to the specification, broad architectural pivots, risky operations, or uncaptured product decisions require human input. Completion requires all specified items and their declared checks to pass.
Testing generated code should use a safe, sandboxed environment. Arbitrary shell commands require safety validation, and code or specifications must not contain hardcoded secrets. Production deployment, data migrations, payments, credential changes, destructive commands, and external writes belong behind the defined approval gates.
Source README
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.
FAQ
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