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qte77/README.md

qte77

qte77 is a governed operating model for an agentic estate. Goals steer top-down, evals trace achievement bottom-up, all built in the open. Not a demo — a model to read, critique, and lift.

What

qte77 runs an agentic estate as a governed loop — intent flows down, proof flows up:

qte77 — the governed loop: GOALS (goals.json OKRs, each KR a pre-committed eval) steer down through ENFORCE + TRACE (the governance spine — eval-gate enforces, goal_id links, rollup proves %) to CODE (the cadence engine — agents open PRs that close KRs); achievement traces back up.

Built from polyforge-orchestrator (dev loop) and office-forge-orchestrator (office loop), reusable engines (doc-pipeline-engine, polyfetch-scrape), and ralph-loop driving the autonomous build-and-improve cycle. Agents propose; humans approve and steer. For how responsibility maps across repos, see the authority chain.

How

Two ways in:

Companion repos live as siblings under qte77.

Why

Run agents across many repos and it drifts into chaos — no shared goals, no traceability, no proof that "done" means "achieved." qte77 is the governance for exactly that: goals steer the work, a pre-committed eval gates every key result, and achievement traces back up — so the estate compounds instead of forgetting.

Built in the open, honestly: the rails ship before the goals, and what's live versus still dormant is shown as it is — see STATUS.md. It's a cross-repo operating model, not a single-repo agent runner; reach for something else if your loop fits in one repo or one prompt.

Refs

License

Apache-2.0 — see LICENSE.

Tools

PythonAstralTypeScriptMarkdownLinuxBashGitGitHub ActionsDockerDev ContainersAzureAWSGoogle CloudROSHugging FaceGitHub ModelsClaudeModel Context Protocol

Posts

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  1. agentic-signal-to-concept agentic-signal-to-concept Public

    Mines public complaint and build signal into grounded product-concept candidates — can be chained into qte77/agentic-market-research-to-gtm for GTM/PMF validation.

    Python

  2. agentic-market-research-to-gtm agentic-market-research-to-gtm Public

    Stop Guessing. Start Dominating. - Automated market intelligence for AI startups that refuse to fail

    Makefile 2

  3. agentic-grounded-persona-eval agentic-grounded-persona-eval Public

    Grounds simulated-user personas in sourced real evidence (HN/ProductHunt quotes), then has them live-evaluate the actual product — no invented personas, no guessed pain points.

    Python

  4. context-engineering-template-legacy context-engineering-template-legacy Public archive

    This project aims to implement a template for context engineering with coding agents.

    Makefile 11 1

  5. agenthud-agui-a2ui agenthud-agui-a2ui Public

    AG-UI event replay + A2UI component rendering in a Vite/React app.

    TypeScript 1

  6. ldnmxx-hack ldnmxx-hack Public

    A config-driven agent that streams its own UI. On a single Cloudflare Worker, the model paints a live A2UI interface — not just text — and swap a JSON, swap the app.

    TypeScript