Install
$ agentstack add skill-asaf-dahan-super-skill-template ✓ 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
Super Skill - Agent Entry Point
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 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 LOG.md - change log and audit trail experts/COUNCIL.md - active expert council and debates traces/ - execution traces for causal reasoning wiki/graph.json - domain structure map (optional; run /ss-graph to generate)
Individual expert profiles (experts/[name].md) load on demand only, not by default. Load them when a specific expert's perspective is needed.
Evidence Routing
Before proposing any change, load the files most likely to contain relevant evidence for your task type. This prevents blind proposals.
| 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 | | Expert disagreement | experts/COUNCIL.md, DECISIONS.md, experts/[name].md |
Load the minimum set. Do not load files not listed for your task type.
How Prompts Work
All prompts live in ONBOARDING.md. Claude Code reads and runs them automatically. Users do not copy prompts after the initial Bootstrap setup.
Slash commands: see CLAUDE.md
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
Capabilities
File operations (no shell required)
- Reading and explaining any layer file
- Writing proposals to PENDING.md
- Generating learning content to notebooks/
Shell required
- python scripts/update_summary.py (regenerate SUMMARY.md)
- python scripts/feed_notebook.py (push files to NotebookLM)
- python scripts/generate_learning.py audio | quiz | 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.