Agent Toolkit Landscape

A growing catalog of AI agent toolkits, organized by what they actually do. Not a ranking — a map for choosing the right tool for the right job.

Categories

Skill Marketplaces

Discover, install, and share agent skills. The npm/crates.io of agent capabilities.

skills.sh — open ecosystem for reusable agent skills. npx skills add installs to any of 20+ agents. Leaderboard tracks installs (top skill: 731K installs). Categories: dev (React, Next.js, Postgres), cloud (Azure, Firebase), marketing (SEO, copywriting), productivity (browser automation, docs).

SkillsMP — community directory indexing 700K+ skills from GitHub. Uses the open SKILL.md standard (Anthropic, Dec 2025; adopted by OpenAI for Codex CLI). Filters low-quality repos (min 2 stars), scans for quality. Independent project, not official.

SKILL.md standard: model-invoked (agent decides when to use) vs slash commands (user-invoked). Personal: ~/.claude/skills/. Project: .claude/skills/. Works across Claude Code and Codex CLI.

When to use: before building a custom skill, search these marketplaces. Someone probably already built it.

Prompt Libraries

Collections of agent personalities/prompts. Zero setup, no state, no orchestration.

Agency Agents — 130+ specialists organized by division (engineering, design, marketing, sales, product, testing, PM). Each = markdown file with identity, workflows, deliverables, success metrics. Convert to any platform with one script.

When to use: you need a domain expert you don’t have a skill for (Solidity audit, Chinese market localization, threat detection). Copy a file, go.

Limitation: prompts only. No state, no memory, no pipeline, no quality gates.

Executable Skill Systems

Pipeline-oriented tools that chain multi-step workflows. Skills read previous outputs, write artifacts, enforce quality.

Superpowers (143K stars) — enforced 7-phase development workflow: brainstorming → git worktrees → writing plans → subagent-driven execution → TDD → code review → finish branch. Key innovations:

• Mandatory, not optional — agent checks for relevant skills before any task
• Subagent-driven development — fresh agent instance per task prevents context drift, two-stage review (spec compliance → code quality)
• Plans for a “junior engineer” — 2-5 min tasks with exact file paths, complete code, no ambiguity
• TDD enforced — deletes code written before tests
• Cross-platform — Claude Code, Cursor, Copilot CLI, Codex, Gemini CLI, OpenCode

vs solo-factory: Superpowers focuses on the development workflow (plan → code → test → review). solo-factory covers the full product lifecycle (research → validate → scaffold → build → deploy → launch → promote). Superpowers has better cross-platform support; solo-factory has business/marketing skills. Complementary — use Superpowers for code quality, solo-factory for product strategy.

solo-factory — 30 executable skills in 4 phases:

• Analysis (5): /research, /swarm, /validate, /stream, /you2idea-extract
• Development (6): /scaffold, /setup, /plan, /build, /deploy, /review
• Promotion (11): /launch, /landing-gen, /content-gen, /video-promo, /reddit, /seo-audit…
• Utility (8): /init, /factory, /pipeline, /retro, /audit, /memory-audit…

Pipeline: output of one skill is input to next. /pipeline chains automatically. Harness-aware — respects CLAUDE.md, runs tests, follows TDD.

When to use: you’re building a product solo and want the full cycle from idea to launch.

Limitation: Claude Code only. Opinionated methodology (STREAM, S.E.E.D., harness engineering).

Project Managers

Autonomous long-running execution systems. State machines, crash recovery, git isolation.

Symphony (15K stars, OpenAI) — turns project work into isolated, autonomous implementation runs. Teams manage work instead of supervising agents. Elixir-based. Each run is isolated — no context leaking between tasks. OpenAI’s answer to “how to let agents work on real projects.”

GSD-2 (Get Shit Done 2) — autonomous coding agent with hierarchical project management:

• Milestone → shippable version (4-10 slices)
• Slice → demoable vertical capability (1-7 tasks)
• Task → single context-window unit of work

Key capabilities:

• Fresh 200K-token context per task (no context pollution)
• SQLite-backed state machine with TOCTOU hardening
• Git worktree isolation per milestone
• Crash recovery via lock files + session forensics
• Stuck detection (sliding-window pattern analysis)
• Parallel multi-worker execution with file-based IPC
• 3 modes: step (/gsd), auto (/gsd auto), headless (CI/cron)
• .gsd/ artifacts: PROJECT.md, DECISIONS.md, KNOWLEDGE.md, RUNTIME.md, STATE.md

vs solo-factory: GSD-2 is a project manager that runs autonomously for hours. solo-factory is a toolkit you invoke per task. GSD-2 manages the execution loop; solo-factory manages the methodology. They could complement each other — solo-factory for what to build, GSD-2 for how to execute.

When to use: you have a clear spec and want autonomous multi-session execution with crash recovery.

Integration & Tool Platforms

Connect agents to external services — 1000+ APIs, auth, sandboxing. The “plumbing” layer.

Composio — powers 1000+ toolkits for AI agents: GitHub, Slack, Gmail, Notion, Jira, Salesforce, etc. Handles the hard parts: OAuth/API key authentication, tool search (find right tool from 1000+), context management, sandboxed execution.

Key features:

• Tool search — agent describes what it needs, Composio finds the right tool from 1000+
• Authentication — manages OAuth flows, API keys, token refresh for all integrations
• Sandboxed workbench — safe execution environment for agent actions
• MCP + SSE support — works as MCP server or standalone
• Python + TypeScript — works with LangGraph, CrewAI, AutoGen, Claude, OpenAI

When to use: your agent needs to interact with external services (send emails, create PRs, update CRM, post to Slack). Instead of building each integration, use Composio as the tool layer.

Agent Frameworks

Infrastructure for building custom agents. Maximum flexibility, maximum setup cost.

When to use: you’re building a product that IS an agent system (not using agents to build a product).

Key difference: frameworks = building blocks. Everything else = finished tools.

Memory Systems

Persistent memory that survives between sessions. See agent-memory-architecture for deep dive.

When to use: your agent needs to remember across sessions — decisions, preferences, code patterns, user context.

Comparison Matrix

The Layered Stack

These aren’t competing — they’re layers:

1. Memory — Solograph / MemPalace for persistence
2. Skills — solo-factory for methodology (what to build, in what order)
3. Execution — GSD-2 for autonomous long-running tasks
4. Specialists — Agency Agents for domain experts on demand
5. Harness — CLAUDE.md + linters + hooks tying it all together

The harness loop applies to all layers: agent mistake → fix the harness.

See Also

• project-solo-factory — our executable skill system
• agent-memory-architecture — memory layer deep dive (4 types, 3 loops, 5 systems)
• harness-engineering-summary — the discipline that makes any toolkit reliable
• context-engineering — how to feed context to agents regardless of toolkit

Catalog is growing. Last updated: 2026-04-09.