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How It Works

From a requirement to reliable software — the loop your AI coding agent runs every time.

The reliability loop

Five stages keep the work honest from idea to merge. Nothing gets generated without a spec, grounded without your code, or shipped without verification.

01

Specify

Socratic spec engine: requirements, design, and tasks with an approval gate.

02

Ground

RAG retrieval cites your code so the agent doesn't invent APIs.

03

Build

17 multi-stage workflows: review, tests, bug prediction, refactor.

04

Remember

Cross-session memory and a lessons corpus surface what worked before.

05

Verify

Fact-check generated content: imports, flags, links, counts — all real.

What's working underneath

Four pillars power every stage of the loop — each a real, shipped capability.

AI workflows

Specialist teams, not one prompt

17 multi-stage workflows run teams of 2–6 Claude subagents to review code, surface vulnerabilities, generate tests, and plan refactors — with cost-tiered model routing.

  • Security audit, code review, bug prediction, release prep
  • Cheap / capable / premium model routing
  • Structured, readable reports
Project memory

Your agent stops starting from zero

Findings from each session are stashed and recalled in the next. A retrievable lessons corpus surfaces the right engineering lesson at the moment a prompt needs it.

  • Local-first by default — no cloud required
  • Optional Redis semantic tier (local Ollama embeddings)
  • Automatic recall, or on demand with /recall
Retrieval grounding

Answers anchored to your code

Keyword + semantic retrieval keeps generated content grounded in your actual source. Mean faithfulness ≥ 0.97, CI-gated — drift fails the build.

  • Powered by attune-rag — built in, no extra install
  • Citations back to source
  • Faithfulness measured, not assumed
Verification

Catch hallucinations before they ship

Fact-check LLM output against source-of-truth: confirm imports import, CLI flags are real, links resolve, and counts match — before the change reaches main.

  • Verifies docs, code, and generated content
  • Closes the loop the spec opened
  • Built from the discipline that runs this project

The Agent Drafts. You Approve. The Platform Verifies.

Reliability isn't a vibe — it's a gate at each end of the work.

📝

The spec gate

  • Requirements, design, and tasks are written and approved before a line of code
  • Socratic discovery scopes the work with you, not around you
  • The spec is the contract the build is measured against

The verification gate

  • Generated claims are fact-checked against your real source
  • Imports import, CLI flags are real, links resolve, counts match
  • Hallucinations are caught before the change reaches main

Ready to turn requirements into reliable software?

Install from PyPI and run /spec on your next feature.