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## Summary - Migrates roadmaps and RFCs from `blackroad-os-ideas` - Migrates research papers from `blackroad-os-research` - Part of Phase 1 BlackRoad OS consolidation ## Files Added - `docs/roadmap/` - 2025 roadmaps - `docs/rfc/` - RFC templates - `docs/ideas/` - Idea proposals - `docs/papers/` - Research papers (PS-SHA, SIG, finance automation) - `docs/research/` - Research prompts ## Test plan - [ ] Verify docs build - [ ] After merge, archive source repos 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-authored-by: Alexa Louise <YOUR_REAL_EMAIL@EXAMPLE.COM> Co-authored-by: Claude <noreply@anthropic.com>
27 lines
1.6 KiB
Markdown
27 lines
1.6 KiB
Markdown
# SIG Factor Tree
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A SIG factor tree represents an agent or identity as a root node with branches that encode prime factors, attributes, and capabilities. The structure highlights how high-level intent decomposes into actionable, composable traits.
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## Structure
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- **Root (agent/identity):** The anchor of the tree, representing the worldline whose factors are being mapped.
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- **Branches (prime factors):** Core attributes such as mission, constraints, core capabilities, and ethical boundaries. Each branch can be tagged with weights or maturity levels.
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- **Leaves (concrete traits):** Specific skills, datasets, or controls that operationalize each factor. Leaves can point to datasets, models, or policy modules.
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## Mapping to SIG
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- **Angular placement:** Each branch aligns to an angle on the spiral, making categories visually separable.
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- **Radial layering:** Depth in the tree maps to radial distance; inner nodes are foundational, outer leaves are externally visible actions or artifacts.
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- **Composition:** Siblings can combine to form composite capabilities, enabling a readable map of how agents evolve.
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## Uses
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- **Agent identity graphs:** Provide a structured graph that links capabilities to an agent's PS-SHA∞ worldline.
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- **Capability composition:** Help orchestrators decide which capabilities to activate or quarantine when contradictions appear.
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- **Gap analysis:** Identify missing leaves or weak factors for targeted data collection or training.
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## TODOs
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- Define a serialization that aligns with `schemas/sig.schema.json` for automatic visualization.
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- Experiment with scoring factors to generate spiral coordinates for plotting.
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