Reliable AI Delivery System

ACTIVE

Turn AI coding output into evidence-backed delivery

Launched July 17, 2026

About Reliable AI Delivery System

Reliable AI Delivery System is a downloadable collection of Codex skills, tests, and delivery guides that adds a stricter workflow for AI‑generated code. It lets an AI coding agent define a target, keep changes within a bounded scope, debug using observed evidence, verify acceptance criteria, and generate a final report that separates proven work from unverified work. The package includes an orchestrator, five focused skills (Reliable Work Start, Scope Control, Systematic Debugging Guard, Evidence Acceptance, Reliable Delivery Report), ten test cases, a coverage matrix, field‑failure studies, and optional free or standalone skills for evidence auditing.

Pricing

Pricing information isn't available yet.

Capabilities

Orchestrator Coordination

Runs the delivery workflow by invoking five focused Codex skills to manage start, scope, debugging, evidence acceptance, and final reporting.

Reliable Work Start Skill

Initializes a task with defined targets and allowed scope, establishing boundaries for AI‑generated changes.

Scope Control Skill

Enforces scoped changes, preventing out‑of‑bounds modifications and unauthorized actions during coding.

Systematic Debugging Guard Skill

Monitors execution evidence and provides debugging guidance based on observed test results.

Evidence Acceptance Skill

Validates that acceptance criteria are met using concrete test evidence before marking work as complete.

Reliable Delivery Report Skill

Generates a final report that separates verified work from any unverified output for auditability.

AI Completion Evidence Auditor (Free)

Allows post‑completion evidence checking to confirm that reported results are backed by observable data.

AI Coding Delivery Gatekeeper (Paid Standalone)

Provides a single marketplace skill for controlling one AI coding task without the full bundle.

Test Suite

Includes ten test scenarios covering vague requests, scope creep, missing validation, false completions, auth regressions, debugging loops, unauthorized releases, secret exposure, invalid criteria, and handoff interruptions.

Use Cases

Controlled AI Code Delivery
Ensures AI‑generated code stays within defined scope, is debugged with evidence, and meets acceptance criteria before release.
For: Developers, indie hackers, technical founders, consultants, small teams using AI coding agents
Auditable Work Reporting
Creates a final delivery report that separates proven changes from unverified ones, enabling later audit and review.
For: Technical founders and teams needing traceable delivery records
Evidence‑Based Debugging
Provides systematic debugging using test evidence to resolve hidden issues like credential integrity or provider mismatches.
For: Developers handling complex integrations or security‑sensitive components
Standalone Task Governance
Uses the AI Coding Delivery Gatekeeper skill to control a single AI coding task without adopting the full suite.
For: Teams wanting a one‑off controlled workflow for a specific task