Seeded INTENT.md and some basic information.
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AGENTS.md
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AGENTS.md
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# polycode-sim — Agent Instructions
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## Repo Identity
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**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.
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**Domain:** infotech
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**Repo slug:** polycode-sim
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**Topic ID:** `cee7bedf-2b48-46ef-8601-006474f2ad7a`
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**Workplan prefix:** `POLYCODE-WP-`
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---
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## State Hub Integration
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The Custodian State Hub tracks work across all domains. Interact via HTTP REST —
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there is no MCP server for Codex agents.
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| Context | URL |
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|---------|-----|
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| Local workstation | `http://127.0.0.1:8000` |
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| Remote via tunnel | `http://127.0.0.1:18000` |
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| Optional local edge relay | http://127.0.0.1:18080 |
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When an operator has enabled the edge relay, set API_BASE to the relay URL.
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Queueable writes return an explicit queued receipt if the central hub is
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unreachable. Treat that as pending local evidence, then ask the operator to run
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statehub outbox status/replay after connectivity returns.
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### Orient at session start
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```bash
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# Offline brief — works without hub connection
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cat .custodian-brief.md
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# Active workplans for this domain
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curl -s "http://127.0.0.1:8000/workplans/?topic_id=cee7bedf-2b48-46ef-8601-006474f2ad7a&status=active" \
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| python3 -m json.tool
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# Check inbox
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curl -s "http://127.0.0.1:8000/messages/?to_agent=polycode-sim&unread_only=true" \
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| python3 -m json.tool
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```
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Mark a message read:
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```bash
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curl -s -X PATCH "http://127.0.0.1:8000/messages/<id>/read" \
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-H "Content-Type: application/json" -d '{}'
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```
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### Log progress (required at session close)
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```bash
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curl -s -X POST http://127.0.0.1:8000/progress/ \
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-H "Content-Type: application/json" \
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-d '{
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"summary": "what was done",
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"event_type": "note",
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"author": "codex",
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"workplan_id": "<uuid>",
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"task_id": "<uuid>"
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}'
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```
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Omit `workplan_id` / `task_id` when not applicable.
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### Update task status
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```bash
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curl -s -X PATCH "http://127.0.0.1:8000/tasks/<task_id>" \
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-H "Content-Type: application/json" \
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-d '{"status": "progress"}'
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# values: wait | todo | progress | done | cancel
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```
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### Flag a task for human review
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```bash
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curl -s -X PATCH "http://127.0.0.1:8000/tasks/<task_id>" \
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-H "Content-Type: application/json" \
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-d '{"needs_human": true, "intervention_note": "reason"}'
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```
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---
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## Session Protocol
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**Start:**
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1. `cat .custodian-brief.md` — domain goal and open workplans (offline-safe)
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2. Check inbox: `GET /messages/?to_agent=polycode-sim&unread_only=true`; mark read
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3. Scan workplans: `ls workplans/` — note `status: ready`, `active`, or `blocked` files and open tasks
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4. Check human-needed tasks: `GET /tasks/?needs_human=true`
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**During work:**
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- Update task statuses in workplan files as tasks progress
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- Record significant decisions via `POST /decisions/`
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**Close:**
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1. Update workplan file task statuses to reflect progress
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2. Log: `POST /progress/` with a summary of what changed
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3. After workplan file changes, run:
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```bash
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statehub fix-consistency
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```
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Coding agents should run this directly; ask the operator only if the CLI or
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State Hub API is unavailable. This syncs task status from files into the hub DB.
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---
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{CREDENTIAL_ROUTING}
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<!-- REPO-AGENTS-EXTENSIONS -->
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<!-- Append repo-specific agent instructions below this marker.
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The state-hub template sync preserves content after this line. -->
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---
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## Workplan Convention (ADR-001)
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Work items originate as files in this repo — not in the hub. The hub is a
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read/cache/index layer that rebuilds from files.
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**File location:** `workplans/POLYCODE-WP-NNNN-<slug>.md`
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**Archived location:** finished workplans may move to
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`workplans/archived/YYMMDD-POLYCODE-WP-NNNN-<slug>.md`. The `YYMMDD` prefix is
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the completion/archive date; the frontmatter `id` does not change.
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**Ad Hoc Tasks:** small opportunistic fixes discovered during a session use
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`workplans/ADHOC-YYYY-MM-DD.md` with task ids `ADHOC-YYYY-MM-DD-T01`, etc. Use
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this only for low-risk work completed directly; create a normal workplan for
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anything needing analysis, design, approval, dependencies, or multiple phases.
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**Frontmatter:**
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```yaml
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---
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id: POLYCODE-WP-NNNN
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type: workplan
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title: "..."
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domain: infotech
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repo: polycode-sim
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status: proposed | ready | active | blocked | backlog | finished | archived
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owner: codex
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topic_slug: ...
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created: "YYYY-MM-DD"
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updated: "YYYY-MM-DD"
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state_hub_workstream_id: "<uuid>" # written by fix-consistency — do not edit (legacy name; holds the workplan id)
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---
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```
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Use `proposed` for a new draft, `ready` after review against current repo
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state, and `finished` after implementation. `stalled` and `needs_review` are
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derived health labels, not frontmatter statuses.
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**Task block format** (one per `##` section):
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```
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## Task Title
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` ` `task
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id: POLYCODE-WP-NNNN-T01
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status: wait | todo | progress | done | cancel
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priority: high | medium | low
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state_hub_task_id: "<uuid>" # written by fix-consistency — do not edit
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` ` `
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Task description text.
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```
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Status progression: `todo` → `progress` → `done`; use `wait` for waiting/blocked work and `cancel` for stopped work.
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To create a new workplan:
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1. Write the file following the format above
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2. Run `statehub fix-consistency` locally; ask the operator only if the CLI or
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State Hub API is unavailable.
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23
INTENT.md
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INTENT.md
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**PolyCode Simulator** is a research/prototyping tool for exploring how different stakeholder behaviors affect governance and resource allocation outcomes.
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More concretely:
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**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.
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In practical terms, it should do four things:
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1. **Models actors**
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Investors may allocate capital, back proposals, seek returns, or influence outcomes. Voters may support proposals, delegate votes, behave strategically, or vote based on preferences.
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2. **Models governance/allocation rules**
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It studies how resources, funding, influence, votes, or rewards are distributed under different mechanisms.
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3. **Runs experiments**
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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.
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4. **Aggregates results**
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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.
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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)
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# PolyCode Simulator (v0.1)
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Simulator for PolyCode Market Dynamics
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## Quickstart
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## Quickstart
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1) Run a single demo simulation:
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1) Run a single demo simulation:
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SCOPE.md
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SCOPE.md
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# SCOPE
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> This file was generated by `statehub register`. Refine it as the repository
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> boundaries become clearer.
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## One-liner
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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.
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## Core Idea
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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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## In Scope
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- Core simulation engine for a single demo run
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- Pluggable investor/voter strategy modules
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- Parameter sweeps and KPI aggregation via experiments.py
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- Baseline parameter configuration management
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- Protocol specification documentation
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## Out of Scope
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- Production/live deployment integration
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- Visualization dashboard or UI
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- Cross-repo orchestration
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## Current State
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- {"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"}
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## Getting Oriented
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- Start with: INTENT.md
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- Agent instructions: AGENTS.md
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- Workplans: workplans/
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184
specs/PolyCodePitchDeck
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specs/PolyCodePitchDeck
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PolyCode
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*Predict. Invest. Build. Together.*
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# 📘 PolyCode — Pitch Deck (v0.1)
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---
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## 1. Title Slide
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**PolyCode**
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**The AI-Driven Market Where Code Funds Itself**
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Predict. Invest. Build. Together.
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*(Logo placeholder)*
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---
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## 2. The Problem
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Modern software development is:
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* Slow — coordination and funding bottlenecks stall innovation.
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* Opaque — investors and contributors can’t see progress or ROI until it’s too late.
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* Top-down — product priorities are decided by a few, not by the ecosystem that needs them.
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> **We need a market where ideas compete fairly and resources flow to what proves valuable.**
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---
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## 3. The Vision
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**PolyCode** transforms software creation into a self-financing, self-correcting economy.
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A decentralized platform where:
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* Ideas are posted as *issues*.
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* Users invest and predict the effort required.
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* AI agents implement once funding thresholds are met.
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* Adoption validates success and triggers automatic payouts.
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> **Software builds itself — guided by markets, not managers.**
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---
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## 4. How It Works (Simplified Flow)
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1️⃣ **Post an Idea**
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→ Anyone creates an issue (feature, fix, or concept).
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2️⃣ **Invest & Predict**
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→ Backers fund the idea and bet on required effort + time.
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3️⃣ **AI Implementation Begins**
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→ When funding exceeds predicted effort, PolyCode assigns it to an AI developer instance.
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4️⃣ **Community Votes on Decisions**
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→ AI proposes variants; investors vote.
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5️⃣ **Control Point Review**
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→ At 50% budget use, progress is published — investors can withdraw or double down.
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6️⃣ **Deployment & Adoption Test**
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→ Feature released under a flag.
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→ If >50% of users keep it → accepted & payouts distributed.
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---
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## 5. Reward Distribution (Example)
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| Recipient | Share | Motivation |
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| --------------- | ---------------- | -------------------- |
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| Top estimators | 10 % + 5 % + 1 % | Reward accuracy |
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| Issue author | 10 % | Encourage creativity |
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| Decision voters | 8 % | Reward participation |
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| Investors | 50 % | Return on capital |
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| Platform | up to 16 % | Sustain operations |
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---
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## 6. Example Simulation Outcome
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From early **PolyCode Sim v0.1** runs:
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* 75 % of issues reach acceptance threshold.
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* 20 % overspend frequency (indicates healthy risk dispersion).
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* Decision-quality correlation = +0.42 with adoption (market voting works).
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* Manipulation-proxy < 0.1 mean (robust estimate integrity).
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> Simulation validates that **market feedback can guide AI development efficiently**.
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---
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## 7. Technology Stack
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| Layer | Description |
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| -------------------- | ------------------------------------------------------------ |
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| **PolyCode Sim** | Agent-based simulator for economic tuning |
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| **Core Protocol** | Funding, betting, voting, payout logic |
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| **AI Agents** | Claude Code / OpenAI Codex / local LLMs |
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| **Governance Layer** | DAO-like voting & reputation system |
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| **Telemetry** | Live metrics from production feed simulator for optimization |
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---
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## 8. Competitive Landscape
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| Model | Example | Limitations | PolyCode Advantage |
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||||||
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| -------------------- | ------------------ | ------------------------ | ------------------------------- |
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| Freelance Platforms | Upwork, Fiverr | Manual, trust-based | Automated, prediction-verified |
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| Crowdfunding | Kickstarter | No delivery verification | Code shipped + adoption proof |
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| Open Source Bounties | Gitcoin | Low iteration speed | Continuous, AI-assisted cycles |
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| AI Dev Tools | Replit Ghostwriter | No funding market | Integrated economy + governance |
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---
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## 9. Economic Engine
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||||||
|
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.
|
||||||
|
|
||||||
|
> **We’re 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 don’t wait for permission —
|
||||||
|
> they attract belief, code themselves, and prove their worth.”
|
||||||
|
|
||||||
|
**polycode.ai** | *Predict – Invest – Build – Together*
|
||||||
|
|
||||||
|
xxx
|
||||||
59
workplans/POLYCODE-WP-0001-statehub-bootstrap.md
Normal file
59
workplans/POLYCODE-WP-0001-statehub-bootstrap.md
Normal file
|
|
@ -0,0 +1,59 @@
|
||||||
|
---
|
||||||
|
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
|
||||||
|
```
|
||||||
Loading…
Add table
Add a link
Reference in a new issue