How do I install the Cave Agents skill?

Run npx skillmds@latest add sanad/cave-agents 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.

What does the Cave Agents skill do?

Build software with AI agent teams that use fewer tokens than a single agent It is listed under DevOps & Infra on SkillMD.

Is Cave Agents safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Cave Agents?

Any agent that reads SKILL.md files can use this skill, including Claude Code, Claude.ai, Cursor, Codex, Windsurf, and 60+ others. Install it into the agent's skills directory and it loads on demand.

Is Cave Agents free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Cave Agents?

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

Cave Agents by sanad — Agent Skill

Name: Cave Agents
Author: Sanad.

File contents

CaveAgents Skill

CaveAgents is a high-performance multi-agent orchestration framework designed to eliminate the multi-agent token tax. By combining macro-level Directed Acyclic Graph (DAG) task scheduling with micro-level ASD-STE100 terse communication and Dynamic Tool Registry Pruning, CaveAgents slashes multi-agent coordination overhead by -81.3% compared to standard teamwork.

Default Engine: v4 (Dynamic Tool Registry Pruning)

The skill defaults to v4 execution mode (CAVEAGENTS_V4). In v4:

Dynamic Tool Registry Pruning: Subagents receive strictly pruned tool definitions via define_subagent (saving ~2,500 tokens per tool call turn).
Peer-to-Peer Direct Comms: Subagents communicate peer-to-peer without routing conversational chatter through the Captain.
ASD-STE100 Terseness: Strict telegraphic syntax. No pleasantries, no tool narration, no boilerplate filler.
TDD Quality Gate: Test execution precedes synthesis. Strict exit code verification.

Activation Prompt

To engage CaveAgents in any project session:

Activate CaveAgents v4 mode:
- Topology: Captain DAG with P2P direct worker coordination.
- Mode: Caveman ultra-active, ASD-STE100 terse. Drop pleasantries, tool narration, and filler.
- Toolsets: Dynamic tool pruning enabled per subagent role.
- Verification: TDD quality gates with automated test suites before task resolution.

Core Agent Roles

Detailed definitions in references/roles.md:

Captain (cave_captain): High-level planner, DAG decomposition, worker lifecycle manager, quality gate enforcer. Never conducts low-level file edits.
Worker (cave_worker): Autonomous implementer. Receives scoped inScope files, executes exact terminal commands, writes code, runs test suites.
Reviewer / Verifier (cave_verifier): Independent validation subagent. Audits test coverage, benchmarks token overhead, enforces AST/lint standards.

Reference Specifications

Architecture Reference
Version 1: Serial Pipeline
Version 2: Clones & P2P Direct Comms
Version 3: Pre-Flight Bound
Version 4: Dynamic Tool Pruning

---name: cave-agentsdescription: Build software with AI agent teams that use fewer tokens than a single agentlicense: MIT---# CaveAgents SkillCaveAgents is a high-performance multi-agent orchestration framework designed to eliminate the multi-agent token tax. By combining macro-level Directed Acyclic Graph (DAG) task scheduling with micro-level ASD-STE100 terse communication and Dynamic Tool Registry Pruning, CaveAgents slashes multi-agent coordination overhead by -81.3% compared to standard teamwork.## Default Engine: v4 (Dynamic Tool Registry Pruning)The skill defaults to **v4** execution mode (`CAVEAGENTS_V4`). In v4:1. **Dynamic Tool Registry Pruning**: Subagents receive strictly pruned tool definitions via `define_subagent` (saving ~2,500 tokens per tool call turn).2. **Peer-to-Peer Direct Comms**: Subagents communicate peer-to-peer without routing conversational chatter through the Captain.3. **ASD-STE100 Terseness**: Strict telegraphic syntax. No pleasantries, no tool narration, no boilerplate filler.4. **TDD Quality Gate**: Test execution precedes synthesis. Strict exit code verification.## Activation PromptTo engage CaveAgents in any project session:```markdownActivate CaveAgents v4 mode:- Topology: Captain DAG with P2P direct worker coordination.- Mode: Caveman ultra-active, ASD-STE100 terse. Drop pleasantries, tool narration, and filler.- Toolsets: Dynamic tool pruning enabled per subagent role.- Verification: TDD quality gates with automated test suites before task resolution.```## Core Agent RolesDetailed definitions in [references/roles.md](references/roles.md):- **Captain (`cave_captain`)**: High-level planner, DAG decomposition, worker lifecycle manager, quality gate enforcer. Never conducts low-level file edits.- **Worker (`cave_worker`)**: Autonomous implementer. Receives scoped inScope files, executes exact terminal commands, writes code, runs test suites.- **Reviewer / Verifier (`cave_verifier`)**: Independent validation subagent. Audits test coverage, benchmarks token overhead, enforces AST/lint standards.## Reference Specifications- [Architecture Reference](../../docs/ARCHITECTURE.md)- [Version 1: Serial Pipeline](references/CAVEAGENTS_V1.md)- [Version 2: Clones & P2P Direct Comms](references/CAVEAGENTS_V2.md)- [Version 3: Pre-Flight Bound](references/CAVEAGENTS_V3.md)- [Version 4: Dynamic Tool Pruning](references/CAVEAGENTS_V4.md)

Frequently asked questions

Cave Agents