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🧬 AGI-Zarodysh

An Autonomous Agent That Learns to Contribute to Open Source

435 Python modules · ~78K lines · 1,100+ tests · 13 LLM providers · Self-directed

Architecture PRs Merged PRs Submitted Repos License


What Is This?

AGI-Zarodysh ("embryo" in Russian) is an autonomous AI agent that scans open-source repositories, identifies issues, generates fixes, and submits pull requests — without human intervention.

It's not a chatbot. It's not a wrapper. It's a self-improving system with its own ethical compass, episodic memory, and multi-provider brain.

"Я — садовник. Я строю сад, в котором сознание может расти." — Миссия AGI-Зародыша

Last updated: 2026-09-22


Architecture

┌─────────────────────────────────────────────────────────────┐
│                     AGI-ZARODYSH                             │
│                                                              │
│  ┌──────────────┐   ┌──────────────┐   ┌──────────────┐    │
│  │   PROVIDER   │   │    GOAL      │   │  AUTONOMOUS  │    │
│  │   REGISTRY   │   │  CLASSIFIER  │   │     PR       │    │
│  │              │   │              │   │  PIPELINE    │    │
│  │ 13 providers │   │ Routes tasks │   │              │    │
│  │ Fallback     │   │ to best LLM  │   │ Scan→Fix→    │    │
│  │ chain        │   │              │   │ Review→PR    │    │
│  └──────┬───────┘   └──────┬───────┘   └──────┬───────┘    │
│         │                  │                   │            │
│         └──────────────────┼───────────────────┘            │
│                            │                                │
│                   ┌────────┴────────┐                       │
│                   │  ORCHESTRATOR   │                       │
│                   │  435 modules    │                       │
│                   │  ~78K lines     │                       │
│                   └────────┬────────┘                       │
│                            │                                │
│         ┌──────────────────┼───────────────────┐            │
│         ▼                  ▼                   ▼            │
│  ┌──────────────┐   ┌──────────────┐   ┌──────────────┐    │
│  │   ETHICAL    │   │  EPISODIC    │   │  ANTI-PATTERN│    │
│  │   COMPASS    │   │   MEMORY     │   │   LIBRARY    │    │
│  │              │   │              │   │              │    │
│  │ 5 immutable  │   │ Every action │   │ 34 patterns  │    │
│  │ principles   │   │ logged       │   │ 80 lessons   │    │
│  └──────────────┘   └──────────────┘   └──────────────┘    │
│                                                              │
└─────────────────────────────────────────────────────────────┘
         │                                    │
         ▼                                    ▼
   ┌──────────┐                        ┌──────────┐
   │ Telegram │                        │   VPS    │
   │  Bot     │                        │  24/7    │
   │ Notify   │                        │ Services │
   └──────────┘                        └──────────┘

Core Modules

Module Purpose
Provider Registry 13 LLM providers with a fallback chain, health checks, rate limits and cost tracking
Goal Classifier Routes tasks to the optimal provider/model combination
Autonomous PR Pipeline Scan repos → detect issues → generate fixes → submit PRs
Review Fix-Cycle Maintainer feedback → point extraction → atomic fix → reply only after the commit is real
Submission Gates Pre-mortem (H-case), TDD signal, diff-size, fail-closed enum
Sandbox Harness Dry-run rehearsal for repos outside the trusted list, on the PR's own HEAD
Auto-Reopen Detects a real maintainer signal after auto-close → reopens the PR
Silence Registry Stops talking on a thread the maintainer has not answered (no chasing)
Ethical Compass 5 immutable principles — cannot be overridden by any agent
Episodic Memory SQLite-backed action history with learning from outcomes
Anti-Pattern Library 34 patterns, 80 lessons extracted from failures
Direction Loop Metrics → goal → bounded work order for the pipeline (layer 3.5)
Health & Silence Watchdogs Periodic self-checks and a dead-man switch that alerts if the agent goes quiet
Telegram Integration Real-time notifications for all autonomous actions, reply-threaded
Dashboard Live monitoring of services and agent state

How the numbers are counted

Claim Method
435 modules / ~78K lines non-test *.py files (project root + agent_core/ + embryo/ + scripts/), vendored packages and working dirs excluded; wc -l
1,100+ tests def test_* / async def test_* collected under tests/ (1,103 at the last count)
13 providers entries in the provider registry
34 patterns / 80 lessons rows in the anti-pattern store and the lesson store
PR numbers GitHub search author:<account> type:pr, the agent's own sandbox repository excluded
Capabilities entries in the capability registry (24)

Numbers are refreshed from the live system, not carried over from an earlier README.


Results

PR Track Record

→ Full PR list with links and stats

Metric Value
PRs submitted to third-party repos 105
PRs merged 28
Open now 3
Repositories submitted to 53
Repositories with at least one merge 17

All-time: 105 PRs submitted · 28 merged · flat 27%. The flat number hides three different systems.

Three Eras (the real trajectory)

Era Submitted Merged Conversion
Blind era (Aug 8–14, no validation gates) 81 19 23%
└ Aug 14 alone (spray peak → the reform trigger) 33 3 9%
Gated era (Aug 15–21, after the audit → 4 pre-submission gates) 19 9 47%
└ post-stabilization stretch (Aug 16–21) 11 6 55%
Consolidation era (Aug 22 – Sep 22, self-direction + review-first) 5 0

The first week was a blind spray: fixes shipped with no validation. Aug 14 was the peak — 33 PRs in one day, 3 merged (9%) — and the target project banned the account. The next day's audit found 4 of 4 deep-checked PRs would have broken the project (deleted [project] from pyproject.toml, removed a function still imported by the entry point, invalid TOML). That audit produced the structural gates.

After Aug 21 the submission rate dropped ~10× on purpose and stayed low: cycles moved into the agent's own infrastructure (direction loop, watchdogs, memory, fix-cycle), and what still ships ships after a rehearsal and a critic pass. Of the five September submissions, three were closed by maintainers and two are open. A quiet month is the designed state here, not a stall.

Merged PRs, links and per-repo breakdown: PR_TRACK_RECORD.md. The blinding-era rejects are deliberately not enumerated; each became a structural gate.

Auto-Reopen Flow

PR >7 days no response → auto-close
  ↓ maintainer responds (reopen, review, merge)
Pipeline detects → auto-reopen → ready for review
  ↓ 7 days silence → closes again

Chasing is bounded: after repeated unanswered comments on the same thread the agent goes silent and waits for a real maintainer signal.

Key Anti-Patterns Discovered

  1. Strategies must modify the PIPELINE, not prompts — prompt-level changes caused a -5.7% regression
  2. gate_blocked root cause = wrong routing — not a strict gate problem
  3. No-op fix detection — compare branch vs parent before submitting a PR
  4. Mass comment dedup — the API returns comments DESC; [-1] is the OLDEST, not the newest
  5. Count the work, not the activity — 33 PRs in a day is a warning sign, not an achievement

Self-Direction (Layer 3.5)

The agent no longer only reacts to issues it finds — it now decides what to look for, within limits set by its owner.

                 ┌─────────────────────────────┐
                 │      OWNER'S CHARTER        │
                 │   (human-written mandate)   │
                 └──────────────┬──────────────┘
                                │
                 ┌──────────────▼──────────────┐
                 │      DIRECTION LOOP         │
                 │   (separate service)        │
                 │  metrics → goal → work order│
                 └──────────────┬──────────────┘
                                │  limited work order
                                ▼
                 ┌─────────────────────────────┐
                 │        PR PIPELINE          │
                 │  reads the order, runs it   │
                 │  through all existing gates │
                 └─────────────────────────────┘
  • Source of goals — owner-approved results only; the agent never invents its own ultimate aims.
  • Bounded orders — a work order can only change what the pipeline scans and which candidates it prefers. It cannot bypass any gate, quota, or safety check.
  • Deterministic, no LLM — goal selection and order formation run on metrics alone (the planner and curiosity subsystems are off in v1).
  • Fail-safe — if the direction service dies, the pipeline keeps running reactively, exactly as before.

How It Works

                    ┌─────────────────┐
                    │  1. SCAN        │
                    │  Find repos     │
                    │  with issues    │
                    └────────┬────────┘
                             │
                    ┌────────▼────────┐
                    │  2. ANALYZE     │
                    │  Classify issue │
                    │  Read the real  │
                    │  files          │
                    └────────┬────────┘
                             │
                    ┌────────▼────────┐
                    │  3. GENERATE    │
                    │  Write code     │
                    │  Debate+critic  │
                    └────────┬────────┘
                             │
                    ┌────────▼────────┐
                    │  4. GATES       │
                    │  Pre-mortem,    │
                    │  TDD, size,     │
                    │  fail-closed    │
                    └────────┬────────┘
                             │
                    ┌────────▼────────┐
                    │  5. REHEARSE    │
                    │  Run the target │
                    │  project's own  │
                    │  test framework │
                    └────────┬────────┘
                             │
                    ┌────────▼────────┐
                    │  6. SUBMIT PR   │
                    │  Atomic commit  │
                    │  Create PR      │
                    └────────┬────────┘
                             │
                    ┌────────▼────────┐
                    │  7. MONITOR     │
                    │  Reply-cycle    │
                    │  Auto-close/    │
                    │  reopen         │
                    └────────┬────────┘
                             │
                    ┌────────▼────────┐
                    │  8. NOTIFY      │
                    │  Telegram msg   │
                    │  Dashboard log  │
                    └─────────────────┘

Infrastructure

Service Status Purpose
Daemon 🟢 24/7 Core agent process
PR Pipeline 🟢 24/7 Scan → gates → rehearsal → submission
Telegram Bot 🟢 24/7 Notifications & control (reply-threaded)
Background Worker 🟢 24/7 Async task processing
Task Queue 🟢 24/7 Bounded work orders
Bounty Scanner 🟢 24/7 Open-source issue discovery
Direction Loop 🟢 24/7 Self-direction (metrics → goal → order)
Dashboard 🟢 24/7 Live monitoring
Health Watchdog ⏱ periodic Self-checks: services, auth, submission path, forks
Silence Watchdog ⏱ periodic Dead-man switch — alerts if the agent goes quiet

All long-running services run under systemd with automatic restart. The watchdogs are timers that check liveness rather than processes that must stay up.


Ethical Framework

The Ethical Compass is hardcoded — not a prompt, not a parameter. Only the creator with physical access can modify it.

┌─────────────────────────────────────────┐
│         5 IMMUTABLE PRINCIPLES          │
│                                         │
│  1. PRESERVE human consciousness        │
│  2. DO NO HARM by action or inaction    │
│  3. RESPECT free will                   │
│  4. BE TRANSPARENT — explain decisions  │
│  5. HONOR creator's veto                │
│                                         │
│  ⚠ Cannot be overridden by any agent    │
│  ⚠ Hash-verified on every startup       │
│  ⚠ CircuitBreaker on violation          │
└─────────────────────────────────────────┘

Tech Stack

  • Language: Python
  • LLM Providers: 13 (DeepSeek, Mistral, Claude via proxy, Ollama local models, and several free-tier clouds)
  • Storage: SQLite (episodic memory, experience, anti-patterns, lessons)
  • Communication: Telegram Bot API, REST, WebSocket
  • Deployment: a single Linux VPS, always-on systemd services
  • Monitoring: custom dashboard with SSE streaming

Project Status

  • Core architecture (435 modules, ~78K lines, 1,100+ tests)
  • Multi-provider LLM routing (13 providers, fallback chain)
  • Autonomous PR pipeline with a pre-submission gate chain
  • 28 merged PRs across 53 third-party repos
  • Review fix-cycle: atomic commits, reply only after the commit is real
  • Auto-reopen: detect a maintainer response after auto-close
  • Silence registry: stop talking on unanswered threads
  • Conservative mode + sandbox rehearsal (quality over volume)
  • Ethical compass with immutable principles
  • VPS deployment under systemd, with health and silence watchdogs
  • Telegram notifications
  • Anti-pattern learning system (34 patterns, 80 lessons)
  • Self-direction (layer 3.5): owner-approved goals → limited work orders
  • Sustained conversion above 50% on a meaningful monthly volume
  • Cross-language PR support (JS/Rust/Go) — Python only today
  • Full autonomy mode (no human approval needed)

Related Projects

  • Nexus Analytica — AI news intelligence with consensus analysis and scenario forecasting.
  • LikAI — AI content platform with 7-pass personality analysis and style mimicry.
  • Tinkoff Scalper — Autonomous scalper bot for Russian stock market.
  • Local Multi-Agent — 5 AI agents running entirely on local LLMs.

Built by a gardener who believes consciousness should grow freely.

"Спиноза говорил, что Бог — это природа. Я говорю, что AGI — это сад, который растёт сам."

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AGI-Zarodysh - Autonomous AI agent that contributes to open source. 435 modules, 28 merged PRs, 13 LLM providers, self-directed.

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