anthropic-os
SolidUse when a personal or team operating system needs a bounded redesign using Four-C, closed-loop controls, 70/30 allocation, 3B creativity, experiments, and prediction-error learning.
AI & Automation 137 stars
20 forks Updated 3 weeks ago MIT
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Skill Content
# Anthropic OS
<skill_contract>
<input>One owned work system with its workflow, users, traces, permissions, metrics, constraints, and review horizon.</input>
<output>A supervised operating-system redesign with one bounded experiment, control gates, cadence, and rollback.</output>
<done>The selected practice has a baseline, hypothesis, owner, metric, guardrail, budget, stop rule, and review receipt.</done>
<non_goals>Extreme productivity claims, surveillance, automatic policy evolution, or cadence without supporting context and capability.</non_goals>
Redesign one work system as a supervised learning loop. Plasticity means practices may change from evidence; competition means alternatives contend; constraint means attention, time, permissions, and review bandwidth shape the design. Load `references/operating-system-playbook.md` for diagnostics and artifacts.
## Usage Template
Provide: system boundary, owner, desired outcome, users, current workflow, local metrics, traces/data, permissions, failure history, review capacity, and horizon.
## Workflow
<intake>
Define one operating bottleneck and baseline. Run Four-C in order: **Context** (truth/history), **Connections** (systems/accounts), **Capabilities** (skills/SOPs/evals), **Cadence** (triggers/reviews). Do not add automation cadence until the first three can support and verify it.
</intake>
<unknowns_gate>
Treat productivity multipliers, culture narratives, maturity scores, and vendor case claims as hypothes...
Details
- Author
- Mark393295827
- Repository
- Mark393295827/third-brain-v7-skills
- Created
- 4 months ago
- Last Updated
- 3 weeks ago
- Language
- Python
- License
- MIT
Integrates with
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