- 8-agent OpenClaw cluster (Manager, Tech-Lead, Secretary, Auditor, Optimizer, Study-Builder, NX-Expert, Webster) - Orchestration engine: orchestrate.py (sync delegation + handoffs) - Workflow engine: YAML-defined multi-step pipelines - Agent workspaces: SOUL.md, AGENTS.md, MEMORY.md per agent - Shared skills: delegate, orchestrate, atomizer-protocols - Capability registry (AGENTS_REGISTRY.json) - Cluster management: cluster.sh, systemd template - All secrets replaced with env var references
10 KiB
📊 Atomizer Dashboard & Reporting System — Master Plan
Status: PROPOSAL | Date: 2026-02-14 | Author: Manager Agent | For: Antoine (CEO)
Executive Summary
A file-based, agent-native dashboard and reporting system that gives Antoine real-time project visibility without leaving the existing Atomizer stack. No new infrastructure—just structured markdown, automated aggregation, and agent-generated reports.
1. Information Architecture
shared/
├── PROJECT_STATUS.md ← Single source of truth (Manager-owned)
├── project_log.md ← Append-only agent activity log
├── dashboards/
│ ├── exec-summary.md ← CEO dashboard (auto-generated)
│ ├── technical.md ← FEA/optimization status
│ └── operations.md ← Agent health, queue, throughput
├── reports/
│ ├── weekly/ ← YYYY-WXX-report.md
│ ├── project/ ← Per-project closeout reports
│ └── templates/ ← Report templates (markdown)
├── data-contracts/
│ └── schemas.md ← Field definitions for all status files
└── kpi/
└── metrics.md ← Rolling KPI tracker
Principle: Everything is markdown. Agents read/write natively. No database, no web server, no maintenance burden.
2. Dashboard Modules
2A. Executive Summary (dashboards/exec-summary.md)
Audience: Antoine | Update frequency: On every PROJECT_STATUS.md change
| Section | Content |
|---|---|
| 🚦 Project RAG | Red/Amber/Green per active project, one line each |
| 📌 Decisions Needed | Items blocked on CEO approval |
| 💰 Resource Burn | Agent token usage / cost estimate (daily/weekly) |
| 🏆 Wins This Week | Completed milestones, delivered studies |
| ⚠️ Top 3 Risks | Highest-impact risks across all projects |
Format: ≤30 lines. Scannable in 60 seconds.
2B. Technical Dashboard (dashboards/technical.md)
Audience: Technical Lead, Optimizer | Update frequency: Per study cycle
| Section | Content |
|---|---|
| Active Studies | Study name, iteration count, best objective, convergence % |
| FEA Queue | Jobs pending / running / completed / failed |
| Model Registry | Active NX models, mesh stats, last validated date |
| Optimization Curves | Tabular: iteration vs objective vs constraint satisfaction |
| Knowledge Base Delta | New entries since last report |
2C. Operations Dashboard (dashboards/operations.md)
Audience: Manager (self-monitoring), Mario (infra) | Update frequency: Hourly via cron or on-demand
| Section | Content |
|---|---|
| Agent Health | Last active timestamp per agent, error count (24h) |
| Message Throughput | Messages processed per agent per day |
| Queue Depth | Pending delegations, blocked tasks |
| Token Budget | Usage vs budget per agent, projected monthly |
| System Alerts | Disk, memory, process status flags |
3. Data Contracts
Every agent writing to project_log.md MUST use this format:
## [YYYY-MM-DD HH:MM] agent-id | project-slug | event-type
**Status:** in-progress | completed | blocked | failed
**Summary:** One-line description
**Detail:** (optional) Multi-line context
**Metrics:** (optional) key=value pairs
**Blockers:** (optional) What's blocking and who can unblock
---
Event Types (enumerated)
| Type | Meaning |
|---|---|
study-start |
New optimization study launched |
study-iteration |
Iteration completed with results |
study-complete |
Study converged or terminated |
review-request |
Deliverable ready for review |
decision-needed |
CEO/human input required |
task-delegated |
Work handed to another agent |
task-completed |
Delegated work finished |
error |
Something failed |
milestone |
Phase/gate achieved |
Dashboard Field Schema
Each dashboard section maps to specific log event types. Manager agent aggregates—no other agent touches dashboard files directly.
4. Report System
4A. Weekly Report (auto-generated every Friday or on-demand)
Template: reports/templates/weekly-template.md
# Atomizer Weekly Report — YYYY-WXX
## Highlights
- (auto: completed milestones from log)
## Projects
### [Project Name]
- Status: RAG
- This week: (auto: summary of log entries)
- Next week: (auto: from PROJECT_STATUS.md planned items)
- Blockers: (auto: open blockers)
## KPIs
| Metric | This Week | Last Week | Trend |
|--------|-----------|-----------|-------|
## Agent Performance
| Agent | Messages | Tasks Done | Errors | Avg Response |
|-------|----------|------------|--------|-------------|
## Decisions Log
- (auto: from decision-needed events + resolutions)
4B. Project Closeout Report
Generated when a project reaches completed status. Includes full decision trail, final results, lessons learned, KB entries created.
4C. On-Demand Reports
Antoine can request via Discord: "Give me a status report on [project]" → Manager generates from log + status files instantly.
4D. PDF Generation
Use existing atomaste-reports skill for client-facing PDF output when needed.
5. Documentation Governance
Two-Tier System
| Tier | Location | Owner | Mutability |
|---|---|---|---|
| Foundational | context-docs/ |
Mario + Antoine | Immutable by agents. Amended only via CEO-approved change request. |
| Project-Specific | shared/, memory/projects/ |
Manager (gatekeeper), agents (contributors) | Living documents. Agents write, Manager curates. |
Rules
- Foundational docs (00-05, SOUL.md, protocols) = constitution. Agents reference, never edit.
- Project docs = operational. Agents append to log; Manager synthesizes into status files.
- Dashboards = derived. Auto-generated from project docs. Never manually edited.
- Reports = snapshots. Immutable once generated. Stored chronologically.
- Knowledge Base = accumulative. Grows per project via
cad_kb.py. Never pruned without review.
Change Control
- Protocol changes → Antoine approval → Mario implements → agents reload
- Dashboard schema changes → Manager proposes → Antoine approves → Manager implements
- New event types → Manager adds to
schemas.md→ notifies all agents via cluster message
6. Rollout Phases
| Phase | When | What | Gate |
|---|---|---|---|
| R0: Schema | Week 1 | Create data-contracts/schemas.md, reports/templates/, directory structure |
Manager reviews, Antoine approves structure |
| R1: Logging | Week 1-2 | All active agents adopt structured log format in project_log.md |
48h of clean structured logs from all agents |
| R2: Exec Dashboard | Week 2 | Manager auto-generates exec-summary.md from logs |
Antoine confirms it's useful and accurate |
| R3: Tech + Ops Dashboards | Week 3 | Technical and operations dashboards go live | Tech Lead validates technical dashboard accuracy |
| R4: Weekly Reports | Week 3-4 | Automated weekly report generation | First 2 weekly reports reviewed by Antoine |
| R5: KPI Tracking | Week 4 | Rolling metrics in kpi/metrics.md |
KPIs match reality for 2 consecutive weeks |
| R6: PDF Reports | Week 5+ | Client-facing report generation via atomaste-reports | First PDF passes Auditor review |
Each phase has a go/no-go gate. No skipping.
7. Risks & Mitigations
| # | Risk | Impact | Likelihood | Mitigation |
|---|---|---|---|---|
| 1 | Log format drift — agents write inconsistent entries | Dashboards break | Medium | Auditor spot-checks weekly; Manager rejects malformed entries |
| 2 | Information overload — exec dashboard becomes too long | Antoine stops reading it | Medium | Hard cap: 30 lines. Ruthless prioritization. |
| 3 | Stale data — dashboards not updated after agent activity | False confidence | High | Manager updates dashboards on every log synthesis cycle |
| 4 | Token cost explosion — dashboard generation burns budget | Budget overrun | Low | Dashboard gen is cheap (small files). Monitor via ops dashboard. |
| 5 | Single point of failure — Manager agent owns all dashboards | Manager down = no visibility | Medium | Raw project_log.md always available; any agent can read it |
| 6 | Scope creep — adding features before basics work | Delayed delivery | High | Strict phase gates. No R3 until R2 is validated. |
| 7 | File conflicts — multiple agents writing simultaneously | Data corruption | Low | Only Manager writes dashboards; log is append-only with timestamps |
8. KPIs & Gate Rules
KPI List
| # | KPI | Target | Measurement |
|---|---|---|---|
| K1 | Dashboard freshness | ≤1h stale | Time since last exec-summary update |
| K2 | Log compliance rate | ≥95% | % of log entries matching schema |
| K3 | Weekly report delivery | 100% on-time | Generated by Friday 17:00 EST |
| K4 | CEO read-time | ≤60 seconds | Exec summary length ≤30 lines |
| K5 | Decision backlog age | ≤48h | Max age of unresolved decision-needed events |
| K6 | Project status accuracy | No surprises | Zero cases where dashboard says green but reality is red |
| K7 | Agent error rate | ≤5% | Failed tasks / total tasks per agent per week |
| K8 | Report generation cost | ≤$2/week | Token cost for all dashboard + report generation |
Gate Rules
| Gate | Criteria | Evaluator |
|---|---|---|
| G1: Schema Approved | Antoine signs off on data contracts + directory structure | Antoine |
| G2: Logging Stable | 48h of compliant logs from all active agents, ≥95% schema compliance | Auditor |
| G3: Exec Dashboard Valid | Antoine confirms dashboard matches his understanding of project state | Antoine |
| G4: Full Dashboards Live | All 3 dashboards updating correctly for 1 week | Manager + Tech Lead |
| G5: Reports Automated | 2 consecutive weekly reports generated without manual intervention | Manager |
| G6: System Mature | All KPIs met for 2 consecutive weeks | Antoine (final sign-off) |
Decision Required
Antoine: Approve this plan to begin R0 (schema creation) immediately, or flag sections needing revision.
Estimated total effort: ~15 agent-hours across 5 weeks. Zero new infrastructure. Zero new dependencies.