Stack Os
A Claude skill from Asaf-Dahan/super-skill.
Install
$ agentstack add skill-asaf-dahan-super-skill-stack-os ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
name: super-skill-stack-os description: > Technical stack domain expert for a solopreneur SaaS operation. Loads full context on infrastructure, hosting, services, tiers, and cross-product dependencies for GreenLedger and PulseLog. Gives any AI agent verified current state before any action. version: "1.0" author: "Tomer Naveh / Raincode Labs" tags:
- infrastructure
- hosting
- technical-stack
- devops
- cloud-services
Super Skill -- Stack OS
Before Any Action
Read these files in this order:
- CONTEXT.md - who owns this, what domain, what goals
- CURRENT_STATE.md - what the domain looks like right now
- PENDING.md - what is waiting for user approval
Never skip this sequence. Context before action, always.
Operating Principle
The model proposes. The user decides. The Super Skill records. The system executes.
Write all proposals and evaluations to PENDING.md. Do not modify any layer file without explicit user approval.
Domain Scope
Products: GreenLedger (sustainability reporting SaaS), PulseLog (uptime and incident logging dashboard) Shared services: DBHost, CDNLayer, GitHub, Anthropic API GreenLedger-specific: UIBuilder, Stripe, Resend PulseLog-specific: AppHost, Streamlit (admin), Python backend
Domain Files
After reading the three required files above, load the remaining layer files as needed for the current task: DOMAIN_MAP.md - structure and sub-domain relationships EVALUATION.md - criteria for evaluating new entrants DECISIONS.md - decisions made and reasoning MONITORING.md - sources to watch for drift LEARNING.md - NotebookLM integration structure traces/ - execution traces for causal reasoning
Evidence Routing
Before proposing any change, load the files most likely to contain relevant evidence for your task type.
| Task type | Evidence files (load in order) | |------------------------------|---------------------------------------------------| | Evaluate a new tool/method | EVALUATION.md, CURRENTSTATE.md, DECISIONS.md | | Propose architecture change | DECISIONS.md, DOMAINMAP.md, CURRENTSTATE.md | | Investigate drift or breakage | MONITORING.md, CURRENTSTATE.md, traces/ | | Resolve a PENDING item | PENDING.md, DECISIONS.md, EVALUATION.md | | Generate learning content | LEARNING.md, CONTEXT.md, CURRENTSTATE.md | | Root-cause analysis | traces/, DECISIONS.md, LOG.md | | Cross-domain impact check | DOMAINMAP.md, CURRENT_STATE.md, DECISIONS.md |
Load the minimum set. Do not load files not listed for your task type.
Learning Generation
To generate learning content from this Super Skill: python scripts/generatelearning.py audio python scripts/generatelearning.py quiz python scripts/generate_learning.py mindmap
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: Asaf-Dahan
- Source: Asaf-Dahan/super-skill
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.