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Agent skills
parallel-agents

Topic: parallel-agents

42 skills in this topic.

agent-orchestrator Open-source, pluggable agentic coding orchestrator. Manages durable coding agents (Claude Code, Codex, OpenCode) through a simple interface — spawn agents, track progress, and let feedback loops like PR reviews and CI failures automatically route to the right agents. Use for fixing bugs, building features, working on GitHub issues, checking status, and managing agent sessions.
ComposioHQ/agent-orchestrator 6,182
brownfield-adoption Step-by-step process for adopting Cavekit on an existing codebase. Covers the 6-step brownfield process, bootstrap prompt design, spec validation against existing behavior, and the decision between brownfield adoption vs deliberate rewrite. Trigger phrases: "brownfield", "existing codebase", "add Cavekit to existing project", "adopt Cavekit", "layer kits on code", "retrofit kits"
JuliusBrussee/cavekit 256
cavekit-writing How to write Cavekit-quality kits that AI agents can consume effectively. Covers implementation-agnostic cavekit design, testable acceptance criteria, hierarchical structure, cross-referencing, cavekit templates, greenfield and rewrite patterns, cavekit compaction, and gap analysis. Trigger phrases: "write kits", "create kits", "cavekit this out", "define requirements for agents", "how to write kits for AI"
JuliusBrussee/cavekit 256
caveman Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested. Integrated into Cavekit: enabled by default for build, inspect, and subagent phases via caveman_mode config. See scripts/bp-config.sh for caveman_mode and caveman_phases.
JuliusBrussee/cavekit 256
context-architecture Progressive disclosure architecture for organizing project context as a DAG (directed acyclic graph). Agents enter at the root and traverse only the subgraph relevant to their task. Covers the 4-tier information flow (refs → kits → plans → impl), CLAUDE.md hierarchy across context/ and source tree, index files as DAG hub nodes, nesting rules, and backward compatibility. Trigger phrases: "context architecture", "progressive disclosure", "organize context for agents", "context directory structure", "how to structure docs for AI", "context hierarchy"
JuliusBrussee/cavekit 256
convergence-monitoring Detecting whether agent iterations are converging toward a stable solution or hitting a ceiling. Covers convergence signals, ceiling detection, non-convergence diagnosis, test pass rate as a convergence metric, and forward progress tracking for large projects. Trigger phrases: "convergence", "is the agent converging", "ceiling detection", "when to stop iterating", "diminishing returns"
JuliusBrussee/cavekit 256
design-system How to write and maintain a DESIGN.md in the 9-section Google Stitch format. Covers the 9-section structure, design token conventions, quality standards, integration with kits and build tasks, revision patterns, and collection import. Trigger phrases: "design system", "DESIGN.md", "visual design spec", "design tokens", "create design system", "import design system", "visual identity", "UI spec", "design language"
JuliusBrussee/cavekit 256
documentation-inversion Inverts the traditional documentation flow from code-to-wiki-for-humans (which rots) into code-to-CLAUDE.md-to-skills-for-agents (which stays current). Each module gets a machine-readable CLAUDE.md, navigation skills teach agents how to explore libraries, and plugins package skills for on-demand loading. Documentation structured for machine consumption -- hierarchical, cross-referenced, with clear entry points -- rather than narrative human reading. This is a fundamental shift: build documentation for agents, not people. Triggers: "documentation inversion", "skills as docs", "living documentation", "docs for agents", "machine-readable docs", "agent-first documentation".
JuliusBrussee/cavekit 256
impl-tracking Implementation tracking documents for maintaining living records of what was built, what is pending, what failed, and what dead ends were explored. Covers the full tracking document template, dead ends prevention, cross-iteration continuity, spec compaction, and inter-session feedback protocol. Trigger phrases: "implementation tracking", "track progress", "session tracking", "what did the agent do", "dead ends", "failed approaches"
JuliusBrussee/cavekit 256
methodology Core Cavekit methodology — the master skill that teaches the Hunt lifecycle and routes to all sub-skills. Covers the Specify Before Building principle, the scientific method analogy, the four-phase Hunt lifecycle, decision matrix for when to use Cavekit, and build pipeline analogy. Trigger phrases: "use Cavekit", "cavekit methodology", "start Cavekit project", "cavekit methodology", "how should I structure this project for AI agents"
JuliusBrussee/cavekit 256
peer-review Patterns for using a second AI agent or model to challenge the primary builder agent's work. Covers six review modes (Diff Critique, Design Challenge, Threaded Debate, Delegated Scrutiny, Deciding Vote, Coverage Audit), how to set up peer review with any model via MCP server, peer review iteration loops that alternate builder and reviewer prompts, and prompt templates for each strategy. The peer reviewer's job is to find what the builder missed, not to agree. Triggers: "peer review", "peer review agent", "use another model to review", "second opinion on code", "cross-model review".
JuliusBrussee/cavekit 256
peer-review-loop Peer Review Ralph Loop — combines Cavekit kits with a Ralph Loop and true cross-model peer review using Codex (OpenAI). Claude builds from specs; Codex reviews adversarially. Primary path: Codex CLI delegation via codex-review.sh (fast, no MCP overhead). Legacy fallback: Codex as MCP server when CLI delegation is unavailable. Covers setup, iteration patterns, convergence detection, and completion criteria. Triggers: "peer review loop", "ralph loop with codex", "cavekit ralph", "peer review build loop", "cross-model loop", "codex peer reviewer", "cavekit to ralph loop"
JuliusBrussee/cavekit 256
prompt-pipeline How to design the numbered prompt pipeline that drives Hunt phases in Cavekit. Covers greenfield 3-prompt patterns, rewrite 6-9 prompt patterns, shared principles, prompt engineering best practices, task templates, and time guards. Trigger phrases: "prompt pipeline", "design prompts for SDD", "create Hunt prompts", "pipeline prompts", "how many prompts do I need"
JuliusBrussee/cavekit 256
revision The technique of tracing bugs and manual fixes back to kits and prompts, then fixing at the source so the iteration loop can reproduce the fix autonomously. Covers the 6-step revision process, commit classification, cavekit-level root cause analysis, and regression test generation. Trigger phrases: "revise", "revision", "trace bug to cavekit", "fix the cavekit not the code", "why did this bug happen", "update kits from bug"
JuliusBrussee/cavekit 256
speculative-pipeline A pipeline execution strategy where downstream stages start before upstream stages finish, using staggered timing with configurable delays. The leader begins first, and followers start after a delay, building from whatever partial output exists. Combined with convergence loops, early follower output self-corrects as upstream artifacts solidify. Cuts total pipeline time dramatically -- a 3-stage pipeline that takes 12 hours sequentially can finish in roughly 7 hours with speculative-pipeline staggering. Triggers: "speculative-pipeline", "staggered pipeline", "parallel prompts with delay", "overlap pipeline stages", "faster pipeline".
JuliusBrussee/cavekit 256
ui-craft Authoritative guide for implementing stunning, accessible, performant UI. Synthesizes design engineering philosophy, accessibility standards, animation principles, spatial design, typography, color systems, and component craft into a single actionable reference. Complements the design-system skill (which covers DESIGN.md spec writing) by covering the HOW of implementation. Trigger phrases: "build UI", "create component", "landing page", "make it look good", "frontend", "design", "polish UI", "implement design", "make it beautiful", "UI implementation", "component styling", "animation", "accessibility"
JuliusBrussee/cavekit 256
validation-first Validation-first design for AI agent output — every spec requirement must be automatically verifiable. Covers the 6-gate validation pipeline, phase gates between Hunt phases, merge protocol, completion signals, and acceptance criteria design patterns. Trigger phrases: "validation gates", "quality gates", "validation-first design", "how to validate agent output", "acceptance criteria design"
JuliusBrussee/cavekit 256
debugging Debug and troubleshoot issues
saadnvd1/agent-os 127