How do I install the Ager Scan skill?

Run npx skillmds@latest add spillwavesolutions/ager-scan in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Ager Scan safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Ager Scan?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Ager Scan free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Ager Scan?

spillwavesolutions (@spillwavesolutions) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Ager Scan by spillwavesolutions — Agent Skill

Name: Ager Scan
Author: spillwavesolutions

Ager Scan

Scan a codebase for agent frameworks (LangGraph, CrewAI, LlamaIndex, Claude/OpenAI APIs, MCP, Deep Agents, hyperscalers, microVMs) and for Claude/Grok/Codex/universal plugin agents and skills. Extracts prompts, tools, schemas, orchestration, loops, harness signals, and plugin frontmatter. Use when reverse-engineering an existing agent project into AGER concepts.

File contents

AGER Scan

Deterministic filesystem scan — the reverse-engineering detector for agent stacks. Sibling of SAC sac-scan / DEKC dekc-walk, specialized for multi-agent runtimes.

What it extracts

Finding kind	Maps toward AGER
plugin	Harness + AgentGraph
agent / skill	WorkerAgent / JudgeAgent / OrchestratorAgent
framework	Framework adapter notes
system_prompt / prompt	AgentNode.instructions / Prompt
tool	Tool + ToolRule
mcp	Tool + JSON-RPC schema
schema	InputSchema / OutputSchema
graph	AgentGraph + ControlEdge
loop	LoopPolicy + LoopControl
orchestration	Orchestrator / Handoff / FanOut / HumanGate
sandbox	ContextIsolationPolicy
hyperscaler	Run + CheckpointPolicy (AgentCore, Azure AI, Vertex)

Supported detectors (non-exhaustive)

Claude Code plugins: .claude-plugin/plugin.json, .claude/agents/*.md, .claude/skills/*/SKILL.md (and undotted claude/)
Grok Build plugins: .grok-plugin/, .grok/agents, .grok/skills (and undotted grok/)
Codex plugins: .codex-plugin/plugin.json, .codex/agents, .codex/skills (and undotted codex/)
Agent Plugins 1.0: root plugin.json ($schema agent-plugins.org) + agents/ + skills/
Raw Claude / Anthropic API, OpenAI API
LangChain, LangGraph, CrewAI, LlamaIndex
OpenAI Agents SDK, Claude Agent SDK, Deep Agents, AutoGen, Semantic Kernel
MCP servers / JSON-RPC tool catalogs
Hyperscalers: Bedrock AgentCore, Azure AI Agents, Vertex Agent Engine
Hardened runtimes: Firecracker microVMs, gVisor, Kata, E2B, hardened containers

Steps

Confirm the source root (repo path or clone).
Run:

python3 "${CLAUDE_PLUGIN_ROOT}/scripts/ager_scan.py" --root "$SOURCE_ROOT" --json -o scan.json

Summarize frameworks + counts for the user.
For materialization into a draft AGER bundle, continue with ager-reverse-engineer.

Notes

Scan is best-effort and confidence-scored; it does not execute untrusted code.
Prefer promoting high-confidence findings via ager-author after human review.
Generic keyword hits (Supervisor / orchestrator role, container isolation, …) collapse to one finding with multiple evidence_paths instead of one node per file. Tool matches without a real identifier (Tool: { json blob }) are dropped.

---name: ager-scandescription: Scan a codebase for agent frameworks (LangGraph, CrewAI, LlamaIndex, Claude/OpenAI APIs, MCP, Deep Agents, hyperscalers, microVMs) and for Claude/Grok/Codex/universal plugin agents and skills. Extracts prompts, tools, schemas, orchestration, loops, harness signals, and plugin frontmatter. Use when reverse-engineering an existing agent project into AGER concepts.---# AGER ScanDeterministic filesystem scan — the reverse-engineering detector for agent stacks.Sibling of SAC `sac-scan` / DEKC `dekc-walk`, specialized for multi-agent runtimes.## What it extracts| Finding kind | Maps toward AGER ||--------------|------------------|| plugin | Harness + AgentGraph || agent / skill | WorkerAgent / JudgeAgent / OrchestratorAgent || framework | Framework adapter notes || system_prompt / prompt | AgentNode.instructions / Prompt || tool | Tool + ToolRule || mcp | Tool + JSON-RPC schema || schema | InputSchema / OutputSchema || graph | AgentGraph + ControlEdge || loop | LoopPolicy + LoopControl || orchestration | Orchestrator / Handoff / FanOut / HumanGate || sandbox | ContextIsolationPolicy || hyperscaler | Run + CheckpointPolicy (AgentCore, Azure AI, Vertex) |## Supported detectors (non-exhaustive)- **Claude Code plugins**: `.claude-plugin/plugin.json`, `.claude/agents/*.md`, `.claude/skills/*/SKILL.md` (and undotted `claude/`)- **Grok Build plugins**: `.grok-plugin/`, `.grok/agents`, `.grok/skills` (and undotted `grok/`)- **Codex plugins**: `.codex-plugin/plugin.json`, `.codex/agents`, `.codex/skills` (and undotted `codex/`)- **Agent Plugins 1.0**: root `plugin.json` (`$schema` agent-plugins.org) + `agents/` + `skills/`- Raw **Claude / Anthropic API**, **OpenAI API**- **LangChain**, **LangGraph**, **CrewAI**, **LlamaIndex**- **OpenAI Agents SDK**, **Claude Agent SDK**, **Deep Agents**, AutoGen, Semantic Kernel- **MCP** servers / JSON-RPC tool catalogs- Hyperscalers: **Bedrock AgentCore**, Azure AI Agents, Vertex Agent Engine- Hardened runtimes: **Firecracker** microVMs, **gVisor**, **Kata**, **E2B**, hardened containers## Steps1. Confirm the source root (repo path or clone).2. Run:```bashpython3 "${CLAUDE_PLUGIN_ROOT}/scripts/ager_scan.py" --root "$SOURCE_ROOT" --json -o scan.json```3. Summarize frameworks + counts for the user.4. For materialization into a draft AGER bundle, continue with **ager-reverse-engineer**.## Notes- Scan is best-effort and confidence-scored; it does not execute untrusted code.- Prefer promoting high-confidence findings via **ager-author** after human review.- Generic keyword hits (`Supervisor / orchestrator role`, container isolation, …) collapse to one finding with multiple `evidence_paths` instead of one node per file. Tool matches without a real identifier (`Tool: { json blob }`) are dropped.

Frequently asked questions