Seeded INTENT.md and some basic information.
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# polycode-sim — Agent Instructions
## Repo Identity
**Purpose:** PolyCode Simulator is a Python-based agent simulation modeling investor and voter strategies to study governance/allocation dynamics, with parameter sweeps and KPI aggregation.
**Domain:** infotech
**Repo slug:** polycode-sim
**Topic ID:** `cee7bedf-2b48-46ef-8601-006474f2ad7a`
**Workplan prefix:** `POLYCODE-WP-`
---
## State Hub Integration
The Custodian State Hub tracks work across all domains. Interact via HTTP REST —
there is no MCP server for Codex agents.
| Context | URL |
|---------|-----|
| Local workstation | `http://127.0.0.1:8000` |
| Remote via tunnel | `http://127.0.0.1:18000` |
| Optional local edge relay | http://127.0.0.1:18080 |
When an operator has enabled the edge relay, set API_BASE to the relay URL.
Queueable writes return an explicit queued receipt if the central hub is
unreachable. Treat that as pending local evidence, then ask the operator to run
statehub outbox status/replay after connectivity returns.
### Orient at session start
```bash
# Offline brief — works without hub connection
cat .custodian-brief.md
# Active workplans for this domain
curl -s "http://127.0.0.1:8000/workplans/?topic_id=cee7bedf-2b48-46ef-8601-006474f2ad7a&status=active" \
| python3 -m json.tool
# Check inbox
curl -s "http://127.0.0.1:8000/messages/?to_agent=polycode-sim&unread_only=true" \
| python3 -m json.tool
```
Mark a message read:
```bash
curl -s -X PATCH "http://127.0.0.1:8000/messages/<id>/read" \
-H "Content-Type: application/json" -d '{}'
```
### Log progress (required at session close)
```bash
curl -s -X POST http://127.0.0.1:8000/progress/ \
-H "Content-Type: application/json" \
-d '{
"summary": "what was done",
"event_type": "note",
"author": "codex",
"workplan_id": "<uuid>",
"task_id": "<uuid>"
}'
```
Omit `workplan_id` / `task_id` when not applicable.
### Update task status
```bash
curl -s -X PATCH "http://127.0.0.1:8000/tasks/<task_id>" \
-H "Content-Type: application/json" \
-d '{"status": "progress"}'
# values: wait | todo | progress | done | cancel
```
### Flag a task for human review
```bash
curl -s -X PATCH "http://127.0.0.1:8000/tasks/<task_id>" \
-H "Content-Type: application/json" \
-d '{"needs_human": true, "intervention_note": "reason"}'
```
---
## Session Protocol
**Start:**
1. `cat .custodian-brief.md` — domain goal and open workplans (offline-safe)
2. Check inbox: `GET /messages/?to_agent=polycode-sim&unread_only=true`; mark read
3. Scan workplans: `ls workplans/` — note `status: ready`, `active`, or `blocked` files and open tasks
4. Check human-needed tasks: `GET /tasks/?needs_human=true`
**During work:**
- Update task statuses in workplan files as tasks progress
- Record significant decisions via `POST /decisions/`
**Close:**
1. Update workplan file task statuses to reflect progress
2. Log: `POST /progress/` with a summary of what changed
3. After workplan file changes, run:
```bash
statehub fix-consistency
```
Coding agents should run this directly; ask the operator only if the CLI or
State Hub API is unavailable. This syncs task status from files into the hub DB.
---
{CREDENTIAL_ROUTING}
<!-- REPO-AGENTS-EXTENSIONS -->
<!-- Append repo-specific agent instructions below this marker.
The state-hub template sync preserves content after this line. -->
---
## Workplan Convention (ADR-001)
Work items originate as files in this repo — not in the hub. The hub is a
read/cache/index layer that rebuilds from files.
**File location:** `workplans/POLYCODE-WP-NNNN-<slug>.md`
**Archived location:** finished workplans may move to
`workplans/archived/YYMMDD-POLYCODE-WP-NNNN-<slug>.md`. The `YYMMDD` prefix is
the completion/archive date; the frontmatter `id` does not change.
**Ad Hoc Tasks:** small opportunistic fixes discovered during a session use
`workplans/ADHOC-YYYY-MM-DD.md` with task ids `ADHOC-YYYY-MM-DD-T01`, etc. Use
this only for low-risk work completed directly; create a normal workplan for
anything needing analysis, design, approval, dependencies, or multiple phases.
**Frontmatter:**
```yaml
---
id: POLYCODE-WP-NNNN
type: workplan
title: "..."
domain: infotech
repo: polycode-sim
status: proposed | ready | active | blocked | backlog | finished | archived
owner: codex
topic_slug: ...
created: "YYYY-MM-DD"
updated: "YYYY-MM-DD"
state_hub_workstream_id: "<uuid>" # written by fix-consistency — do not edit (legacy name; holds the workplan id)
---
```
Use `proposed` for a new draft, `ready` after review against current repo
state, and `finished` after implementation. `stalled` and `needs_review` are
derived health labels, not frontmatter statuses.
**Task block format** (one per `##` section):
```
## Task Title
` ` `task
id: POLYCODE-WP-NNNN-T01
status: wait | todo | progress | done | cancel
priority: high | medium | low
state_hub_task_id: "<uuid>" # written by fix-consistency — do not edit
` ` `
Task description text.
```
Status progression: `todo``progress``done`; use `wait` for waiting/blocked work and `cancel` for stopped work.
To create a new workplan:
1. Write the file following the format above
2. Run `statehub fix-consistency` locally; ask the operator only if the CLI or
State Hub API is unavailable.

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**PolyCode Simulator** is a research/prototyping tool for exploring how different stakeholder behaviors affect governance and resource allocation outcomes.
More concretely:
**PolyCode Simulator** is a Python simulation system where different types of agents, especially **investors** and **voters**, follow configurable strategies. These agents interact inside a modeled governance or allocation environment. By changing parameters repeatedly, the simulator can explore many scenarios and collect KPIs that show how well different governance/allocation mechanisms perform.
In practical terms, it should do four things:
1. **Models actors**
Investors may allocate capital, back proposals, seek returns, or influence outcomes. Voters may support proposals, delegate votes, behave strategically, or vote based on preferences.
2. **Models governance/allocation rules**
It studies how resources, funding, influence, votes, or rewards are distributed under different mechanisms.
3. **Runs experiments**
Parameter sweeps mean it systematically varies assumptions such as number of voters, investor behavior, voting rules, capital distribution, turnout, strategy mix, incentives, or governance thresholds.
4. **Aggregates results**
KPI aggregation means it summarizes outcomes across runs, for example efficiency, fairness, concentration of power, proposal success rate, capital allocation quality, voter satisfaction, resilience, or strategic exploitability.
Polycode is a **simulation laboratory for mechanism design**: a way to test governance and funding systems before deploying them in the real world.

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# PolyCode Simulator (v0.1)
Simulator for PolyCode Market Dynamics
## Quickstart
1) Run a single demo simulation:

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# SCOPE
> This file was generated by `statehub register`. Refine it as the repository
> boundaries become clearer.
## One-liner
PolyCode Simulator is a Python-based agent simulation framework for studying governance and resource-allocation dynamics. It models investor and voter strategies, runs parameterized scenario sweeps, and aggregates KPIs to compare the behavior, robustness, and outcomes of different allocation mechanisms.
## Core Idea
Polycode is a simulation laboratory for mechanism design: a way to test governance and funding systems before deploying them in the real world.
## In Scope
- Core simulation engine for a single demo run
- Pluggable investor/voter strategy modules
- Parameter sweeps and KPI aggregation via experiments.py
- Baseline parameter configuration management
- Protocol specification documentation
## Out of Scope
- Production/live deployment integration
- Visualization dashboard or UI
- Cross-repo orchestration
## Current State
- {"project_description": "PolyCode Simulator is a Python-based agent simulation modeling investor and voter strategies to study governance/allocation dynamics, with parameter sweeps and KPI aggregation.", "intent_markdown": "# Intent\n\n## Purpose\nPolyCode Simulator (v0.1) is a Python simulation engine that models interactions between investor and voter agents under pluggable strategies, used to explore governance and capital-allocation dynamics and their emergent outcomes (KPIs) across parameter sweeps.\n\n## In Scope\n- Core simulation engine (`simulator.py`) running single demo simulations\n- Pluggable investor/voter strategy implementations (`strategies.py`)\n- Parameter sweep / grid-search experiments with KPI aggregation (`experiments.py`)\n- Baseline parameter configuration (`params_default.json`)\n- Protocol specification documentation (`spec.md`)\n- Run outputs written to `./runs/`\n\n## Out of Scope\n- Production deployment or live trading/voting integration\n- UI/dashboard for visualizing results\n- Multi-repo orchestration or external service integration\n\n## Current State\nEarly-stage (v0.1) simulator with a minimal CLI-driven workflow; single initial commit plus a CI smoke workflow.\n", "domain_slug": null, "topic_slug": "polycode-sim", "topic_title": "PolyCode Simulator", "repo_slug": "polycode-sim", "workplan_prefix": "POLYCODE-WP", "in_scope": ["Core simulation engine for a single demo run", "Pluggable investor/voter strategy modules", "Parameter sweeps and KPI aggregation via experiments.py", "Baseline parameter configuration management", "Protocol specification documentation"], "out_of_scope": ["Production/live deployment integration", "Visualization dashboard or UI", "Cross-repo orchestration"], "project_description": "PolyCode Simulator is a Python-based agent simulation modeling investor and voter strategies to study governance/allocation dynamics, with parameter sweeps and KPI aggregation.", "repo_slug": "polycode-sim", "topic_slug": "polycode-sim", "topic_title": "PolyCode Simulator", "workplan_prefix": "POLYCODE-WP"}
## Getting Oriented
- Start with: INTENT.md
- Agent instructions: AGENTS.md
- Workplans: workplans/

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PolyCode
*Predict. Invest. Build. Together.*
# 📘 PolyCode — Pitch Deck (v0.1)
---
## 1. Title Slide
**PolyCode**
**The AI-Driven Market Where Code Funds Itself**
Predict. Invest. Build. Together.
*(Logo placeholder)*
---
## 2. The Problem
Modern software development is:
* Slow — coordination and funding bottlenecks stall innovation.
* Opaque — investors and contributors cant see progress or ROI until its too late.
* Top-down — product priorities are decided by a few, not by the ecosystem that needs them.
> **We need a market where ideas compete fairly and resources flow to what proves valuable.**
---
## 3. The Vision
**PolyCode** transforms software creation into a self-financing, self-correcting economy.
A decentralized platform where:
* Ideas are posted as *issues*.
* Users invest and predict the effort required.
* AI agents implement once funding thresholds are met.
* Adoption validates success and triggers automatic payouts.
> **Software builds itself — guided by markets, not managers.**
---
## 4. How It Works (Simplified Flow)
1⃣ **Post an Idea**
→ Anyone creates an issue (feature, fix, or concept).
2⃣ **Invest & Predict**
→ Backers fund the idea and bet on required effort + time.
3⃣ **AI Implementation Begins**
→ When funding exceeds predicted effort, PolyCode assigns it to an AI developer instance.
4⃣ **Community Votes on Decisions**
→ AI proposes variants; investors vote.
5⃣ **Control Point Review**
→ At 50% budget use, progress is published — investors can withdraw or double down.
6⃣ **Deployment & Adoption Test**
→ Feature released under a flag.
→ If >50% of users keep it → accepted & payouts distributed.
---
## 5. Reward Distribution (Example)
| Recipient | Share | Motivation |
| --------------- | ---------------- | -------------------- |
| Top estimators | 10 % + 5 % + 1 % | Reward accuracy |
| Issue author | 10 % | Encourage creativity |
| Decision voters | 8 % | Reward participation |
| Investors | 50 % | Return on capital |
| Platform | up to 16 % | Sustain operations |
---
## 6. Example Simulation Outcome
From early **PolyCode Sim v0.1** runs:
* 75 % of issues reach acceptance threshold.
* 20 % overspend frequency (indicates healthy risk dispersion).
* Decision-quality correlation = +0.42 with adoption (market voting works).
* Manipulation-proxy < 0.1 mean (robust estimate integrity).
> Simulation validates that **market feedback can guide AI development efficiently**.
---
## 7. Technology Stack
| Layer | Description |
| -------------------- | ------------------------------------------------------------ |
| **PolyCode Sim** | Agent-based simulator for economic tuning |
| **Core Protocol** | Funding, betting, voting, payout logic |
| **AI Agents** | Claude Code / OpenAI Codex / local LLMs |
| **Governance Layer** | DAO-like voting & reputation system |
| **Telemetry** | Live metrics from production feed simulator for optimization |
---
## 8. Competitive Landscape
| Model | Example | Limitations | PolyCode Advantage |
| -------------------- | ------------------ | ------------------------ | ------------------------------- |
| Freelance Platforms | Upwork, Fiverr | Manual, trust-based | Automated, prediction-verified |
| Crowdfunding | Kickstarter | No delivery verification | Code shipped + adoption proof |
| Open Source Bounties | Gitcoin | Low iteration speed | Continuous, AI-assisted cycles |
| AI Dev Tools | Replit Ghostwriter | No funding market | Integrated economy + governance |
---
## 9. Economic Engine
PolyCode introduces **three internal currencies**:
| Token | Function |
| ----------------- | -------------------------------------------------- |
| **$VIBE / $WORK** | Implementation energy — tokens representing effort |
| **$BET** | Prediction stakes for estimating scope and time |
| **$IMPACT** | Earned reputation for successful participation |
A balanced micro-economy ensures liquidity, accountability, and transparent reward flows.
---
## 10. Business Model
1. **Transaction fees** on each completed issue (platform share).
2. **Premium analytics / dashboards** for investors and DAOs.
3. **Enterprise integration** — companies host private PolyCode markets.
4. **Token appreciation** via protocol usage and staking.
---
## 11. Go-to-Market Plan
* **Phase 1:** Closed beta with AI-assisted open-source repos.
* **Phase 2:** Public market for micro-features.
* **Phase 3:** Enterprise & DAO integration.
* **Phase 4:** On-chain economy with live telemetry feedback.
---
## 12. Team & Ecosystem
* **Founder:** Bernd Worsch — Product strategist, hybrid-post innovator, AI systems architect.
* **Core Collaborators:** AI agents, open-source devs, research partners.
* **Allies:** Coulomb ecosystem (Charges & Joules currencies), KaizenAgentic framework.
---
## 13. Traction & Next Steps
✅ Simulation engine operational.
✅ Parameter optimization underway.
🔜 Beta testers onboarding Q1 2026.
🔜 Telemetry loop integration for adaptive tuning.
> **Were validating an entirely new way to build software.**
---
## 14. The Ask
We are seeking:
* **€500 k** pre-seed for platform launch & compliance.
* Partnerships with **AI infrastructure providers** and **early-stage DAOs**.
* Strategic advisors in **game theory**, **token economics**, and **open-source ecosystems**.
---
## 15. Closing
> “In PolyCode, ideas dont wait for permission —
> they attract belief, code themselves, and prove their worth.”
**polycode.ai** | *Predict Invest Build Together*
xxx

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---
id: POLYCODE-WP-0001
type: workplan
title: "Bootstrap State Hub integration"
domain: infotech
repo: polycode-sim
status: ready
owner: codex
topic_slug: custodian
created: "2026-07-08"
updated: "2026-07-08"
state_hub_workstream_id: "05e27f85-6a20-4906-a3c1-633776d6c448"
---
# Bootstrap State Hub integration
PolyCode Simulator is a Python-based agent simulation modeling investor and voter strategies to study governance/allocation dynamics, with parameter sweeps and KPI aggregation.
## Review Generated Integration Files
```task
id: POLYCODE-WP-0001-T01
status: todo
priority: high
state_hub_task_id: "d0f6a1cd-641f-4a63-890c-99bc5c12cc4b"
```
Review `INTENT.md`, `SCOPE.md`, `AGENTS.md`, and `.custodian-brief.md`.
Replace generated placeholders with repo-specific facts where needed.
## Verify Local Developer Workflow
```task
id: POLYCODE-WP-0001-T02
status: todo
priority: high
state_hub_task_id: "6ad22e61-ad4d-4643-ad49-000e41e4959b"
```
Identify the repo's install, test, lint, build, and run commands. Add or refine
those commands in the agent instructions so future coding sessions can verify
changes confidently.
## Seed First Real Workplan
```task
id: POLYCODE-WP-0001-T03
status: todo
priority: medium
state_hub_task_id: "d0d8fea2-28e8-4766-8295-9118a8378c2c"
```
Create the first implementation workplan for the repository's most important
next change. After workplan file updates, run the sync locally from this repo
checkout:
```bash
statehub fix-consistency
```