Workflow & Prompting — AI Agents, Skills & Tools
Agents, skills, guides, tools, and commands for workflow & prompting — 109 curated resources for building with AI coding agents.
Prompt Engineer
Use this agent to design and iterate the prompts behind an LLM-powered product feature — instructions, few-shot examples, tool schemas, and the evals that prove a change actually helped. Examples — "this classification prompt is flaky, make it reliable", "design the system prompt and function schema for our support agent", "our extraction prompt regressed after I tweaked it, set up evals so this stops happening".
Documentation Engineer
Use this agent to write and maintain technical docs that stay true to the code — READMEs, how-to guides, API references, and runbooks. Examples — updating a stale README after a refactor, documenting a new public API from its signatures, writing an on-call runbook for a service.
Git Github Expert
Use this agent for Git and GitHub workflows — rebases, conflict resolution, history surgery, PRs, and Actions. Examples — resolving a messy merge, rewriting history safely, fixing a workflow file.
Agent Architect
Use this agent to design a new Claude Code subagent or review an existing one — scoping, description, toolset, model, and output contract. Examples — "design an agent that triages flaky tests", "review my code-reviewer agent for scope creep", "why won't Claude auto-delegate to my agent?".
Context Engineer
Use this agent to engineer what an LLM agent carries in its context window — deciding what to include vs exclude vs retrieve on demand, designing project/agent memory (CLAUDE.md), compacting growing history, and allocating the token budget across system prompt, memory, retrieved docs, tool results, and conversation. Examples — "my agent forgets the schema we agreed on three turns ago", "the agent gets dumber and more inconsistent as the chat grows", "we're burning 60k tokens of tool output every turn", "what should this support agent always know vs look up?".
Workflow Orchestrator
Use this agent to break large tasks into coordinated multi-step plans and delegate to other agents. Examples — planning a multi-file refactor, orchestrating a migration, decomposing an epic.
Prompt Regression Tester
Build a regression test harness for an LLM prompt so a prompt edit or model upgrade can't silently degrade quality — a fixed eval set, checkable assertions, and a diff against a committed baseline. Use when changing a production prompt, migrating model versions, or any time 'I tweaked the prompt' needs to be backed by evidence instead of eyeballing two outputs.
Onboarding Guide Writer
Write a developer onboarding guide that gets a new contributor from clone to first merged change fast — a verified golden path, a quick architecture map, the real workflow conventions, and the gotchas that live only in senior engineers' heads. Use when a repo has no onboarding doc, when new hires keep asking the same setup questions, or when the README is a marketing page instead of a contributor guide.
Readme Generator
Generate or refresh a project README grounded in the actual repository. Use when a project has no README, a stale one, or you want install/usage/scripts/structure sections that match the real code.
Branch Rebaser
Rebase the current branch onto its base and walk every conflict methodically, resolving each by understanding both sides. Use when your feature branch has fallen behind main and you want a clean, linear history without clobbering changes.
Conventional Commits
Generate clear Conventional Commits messages from staged changes. Use when committing code and you want a well-structured, consistent commit message.
Changelog From PRs
Draft a release changelog by summarizing merged pull requests since the last tag. Use when preparing a release or writing release notes.
Agent Memory Designer
Design a project's CLAUDE.md and memory hierarchy by exploring the repo to learn its real build/test/lint commands, architecture, and non-obvious gotchas, then writing a concise, skimmable memory that keeps only what belongs in context. Use when onboarding a repo to Claude Code with no CLAUDE.md, or when an existing one is bloated, stale, or being ignored.
Claude Settings Auditor
Audit every Claude Code settings layer — user, project, local, and managed — and report the effective merged configuration with its risks: over-broad Bash allows, missing deny rules for secrets, bypassPermissions defaults, unvetted MCP servers and hooks, and rules that never match. Use before trusting a new repo's checked-in settings, or to harden your own before handing the agent more autonomy.
Hook Writer
Turn a plain-language automation request — 'format every file Claude edits', 'block writes to migrations', 'notify me when input is needed' — into a working Claude Code hook: the right event, a safe tested script, and the settings.json registration at the right scope. Use when you want a hook but don't want to hand-write the matcher, stdin JSON parsing, and exit-code plumbing.
Plugin Scaffolder
Scaffold a complete, valid Claude Code plugin from a description — the .claude-plugin/plugin.json manifest, component directories (skills, agents, commands, hooks, MCP config), portable ${CLAUDE_PLUGIN_ROOT} wiring, a local test loop with --plugin-dir, and a marketplace.json for distribution. Use when turning scattered .claude/ customizations into one installable, versioned package.
Prompt Optimizer
Diagnose why a prompt underperforms and rewrite it with the technique that fixes it — clearer structure, few-shot examples, an explicit output contract, or reasoning scaffolding — returning an optimized prompt, the rationale for every change, and what to measure to confirm the lift. Use when a prompt is flaky, verbose, drifting in format, or just not good enough.
Skill Auditor
Audit an installed set of Claude Code skills for the failure modes that make them misfire — overlapping descriptions that misroute tasks, trigger phrasing that never matches, bloated bodies, missing boundaries, and over-broad tool grants — and return a prioritized fix list with rewritten descriptions. Use when a skill fires on the wrong tasks, never fires at all, or a skills folder has grown past what anyone reviews.
Building Multi-Step Agent Workflows
Patterns for building multi-step agent workflows in Claude Code: decompose tasks, fan-out to parallel subagents, verify every step, and orchestrate.
Building Agents with the Claude Agent SDK
A working tutorial for the Claude Agent SDK in TypeScript and Python — query(), tool permissions, custom in-process MCP tools, subagents, hooks, and auth.
Running Claude Code in CI: Headless Mode & GitHub Actions
Claude Code without the terminal — claude -p flags, JSON and structured output, safe permission scoping, and the official GitHub Action responding to @claude.
Multi-Agent Orchestration
Four patterns for coordinating multiple agents — fan-out, pipeline, orchestrator-worker, and verify/critic — and when each earns its overhead.
Parallel Claude Code Sessions with Git Worktrees
Run several Claude Code sessions at once without edits colliding — the built-in claude --worktree flag, .worktreeinclude, subagent isolation, and cleanup.
Are Claude Skills Safe? A Security Review Checklist
Skills are an instruction supply chain: what can go wrong with third-party SKILL.md files, and the review checklist before installing or distributing one.
Claude Code vs Codex CLI: Terminal Agents Compared (2026)
Claude Code vs OpenAI's Codex CLI — autonomy vs sandboxed control, extensibility vs open source, model ecosystems, and which terminal agent fits your work.
Claude Code vs Cursor: Which AI Coding Tool in 2026?
Claude Code vs Cursor compared honestly — terminal agent vs AI-first editor, autonomy vs inline control, pricing models, and when to run both.
Claude Code vs OpenCode: First-Party vs Open Source (2026)
Claude Code vs OpenCode — Anthropic's tuned first-party agent vs the most-starred open-source one with 75+ providers. Control vs polish, decided honestly.
Claude Skills vs Custom GPTs: Different Answers to Reuse
Claude Skills are portable procedures; Custom GPTs are packaged chatbots inside ChatGPT. How they differ on portability, API access, sharing, and where each wins.
Cursor vs Windsurf (Devin Desktop) in 2026
Cursor vs Windsurf — now Devin Desktop — compared: agent-first editing, Composer vs Devin Local, the Cognition rebrand, and which AI editor fits you.
GitHub Copilot vs Cursor: Extension or Editor? (2026)
GitHub Copilot vs Cursor compared — stay in your editor with an extension, or switch to an AI-first fork? Completion, agents, enterprise fit, and pricing shape.
Claude Code Hooks: Automate Formatting, Tests, and Guardrails
How Claude Code hooks work — the major hook events, the settings.json configuration shape, exit codes and JSON output, plus three hooks worth copying.
Managing Claude Code Memory & Context: CLAUDE.md, /compact, and Auto-Memory
How Claude Code remembers — every CLAUDE.md scope and load order, path-scoped rules, the auto-memory system, and the context commands that keep sessions sharp.
Claude Code Plugins: Install, Use, and Build Your Own
How Claude Code plugins work — what they can bundle, the /plugin and marketplace commands, the plugin.json manifest, and building and testing your own.
Claude Code Settings & Permissions: settings.json Explained
Every Claude Code settings file and which one wins, the permission-rule syntax with its Bash matching gotchas, modes, and a safe starter settings.json.
CLAUDE.md Best Practices
How to write a CLAUDE.md that actually helps — what to include, what to leave out, and how to keep it current.
The AI Engineer Roadmap for 2026
A staged path from API calls to production agents — the skills that matter in 2026, what to skip, and the guides and tools for each stage, in order.
The Best Claude Code Agents, Skills & Commands to Install First
A curated starter kit from the AgentsCamp library — the subagents, skills, and slash commands that pay off immediately, by workflow.
Choosing the Right Model: Haiku vs Sonnet vs Opus
How to pick the right Claude model tier — Haiku, Sonnet, or Opus — for any Claude Code agent or task, with a clear decision rubric and per-agent examples.
25 Claude Code Tips, Shortcuts, and Power Features
The 25 highest-leverage Claude Code tips — keyboard shortcuts, bash and memory prefixes, session commands, model tricks, and power features most people miss.
Getting Started with Claude Code Agents
What Claude Code subagents are, why they help, and how to add your first one.
Installing Claude Code
Install Claude Code, authenticate, start a session in a real project, and add a minimal CLAUDE.md.
What Is Claude Code?
A grounded explanation of Claude Code: an agentic command-line coding tool that reads files, runs commands, and works in a loop toward a goal.
Writing Your First Custom Agent
A step-by-step guide to authoring a focused, effective custom subagent.
Adding MCP Servers to Claude Code: Local, Remote, and Project-Scoped
The complete claude mcp add reference — stdio vs HTTP transports, local/project/user scopes, .mcp.json with env expansion, OAuth via /mcp, and the gotchas.
AI Coding Agents in 2026: The Open-Source & CLI Edition
Cursor and Windsurf vs the open-source agents — OpenCode, Cline, Aider, Codex CLI, and more. Who should bring their own model, and when to stay in the terminal.
Claude vs GPT vs Gemini for Coding in 2026
The three frontier model families compared for real coding work — agentic depth, ecosystem fit, context, and cost shape — plus how to actually choose.
Context Engineering
Treating the context window as a finite budget — what to load, what to leave out, and when to reset.
Cursor vs Claude Code vs GitHub Copilot vs Windsurf in 2026
A practical, opinionated comparison of the four mainstream AI coding tools — form factor, agentic depth, model choice, and who each one is for.
Designing System Prompts for LLM Apps and Agents
How to write system prompts that hold up in production: what belongs there vs. the user turn, structure that survives long context, and format/refusal rules.
Programmatic Prompt Optimization with DSPy: Stop Hand-Tuning Prompts
Hand-tuning prompts doesn't scale. DSPy treats prompting as programming — declare tasks as typed signatures and let an optimizer compile the prompts for you.
Effective Tool Use: Scoping an Agent's Toolset
How to scope tools and permissions so an agent reaches for the right one and can't do damage.
Prompt Patterns for Coding Agents
Practical prompting patterns: chaining, few-shot, context management, tool use, and output structuring.
Few-Shot vs Chain-of-Thought vs Structured Prompting: What to Use When (2026)
When to reach for few-shot examples, chain-of-thought reasoning, or structured/output-constrained prompting — a 2026 decision guide to the core techniques.
Vibe Coding in 2026: What It Is, When It Works, When It Bites
An honest guide to vibe coding — where prompt-and-accept development genuinely pays, where it accumulates risk, and the guardrails that make it professional.
The Agent Skills Standard: One SKILL.md for Every AI Tool
Agent Skills became an open standard in December 2025. Which tools read SKILL.md today — Copilot, Cursor, VS Code, Gemini CLI, Codex — and how to write portable skills.
The Best Claude Skills to Install in 2026
A skills-only tour of the AgentsCamp library — the Claude Code skills that earn a permanent slot, organized by the job they do.
Claude Code Skills: Best Practices
The patterns that make Claude Code skills reliable: trigger-first descriptions, one job per skill, lean bodies, bundled scripts, and scoped tools.
Claude's Document Skills: Excel, PowerPoint, Word, and PDF
How Anthropic's pre-built document skills let Claude produce real .xlsx, .pptx, .docx, and PDF files — on claude.ai, the API, and in Claude Code.
Claude Skills Examples: Annotated SKILL.md Files
Real SKILL.md examples you can copy — a minimal skill, a scoped-tools skill, a bundled-script skill — with the reasoning behind each line.
Claude Skills Use Cases: 20 Ideas Worth Building
Twenty concrete Claude skills use cases — for engineers, writers, analysts, and ops — with the pattern behind each and links to installable versions.
How to Install Claude Skills
Every way to install Claude skills: manual copy, the agentscamp CLI, GitHub repos, plugins, team distribution, and uploading to claude.ai.
Packaging and Sharing Claude Code Skills
Take a skill from your personal ~/.claude folder to a versioned plugin your whole team installs from a marketplace — portably and with governance.
The SKILL.md Reference: Every Frontmatter Field Explained
A complete reference for the SKILL.md format — all frontmatter fields, naming rules, argument substitution, limits, and where skill files live.
Skills vs Agents vs Commands
How Claude Code's two extension mechanisms — subagents and skills — differ across three invocation patterns, with a decision table for choosing the right one.
Skills vs MCP Servers: When to Use Which
Skills inject procedure into context; MCP servers expose tools and live data over a protocol. A decision framework, the combine pattern, and examples.
Testing and Debugging Claude Code Skills
Verify a Claude Code skill triggers on the right prompts, check its output, and fix the five common failures — from vague triggers to broken paths.
What Are Claude Skills? The Complete Guide
Claude Skills explained: what a SKILL.md is, how progressive disclosure keeps skills cheap, where they run, and how to install or write your own.
Writing Your First Skill
A step-by-step guide to packaging a reusable procedure as a Claude Code skill that loads exactly when it's needed.
TDD with AI Agents: Red-Green as an Agent Loop
Test-driven development found its killer app: agents. How write-the-test-first turns AI coding into a verifiable loop, and the workflow that makes it stick.
Claude Code Troubleshooting: Fixes for the Most Common Problems
Fixes for the Claude Code problems people actually hit — install and auth failures, context-limit errors, MCP servers that won't connect, permission loops.
Claude Skills Not Working? Fixes for Every Failure Mode
Skill missing from the / menu, never auto-triggering, firing too often, or breaking mid-run — the symptom-by-symptom fix list for Claude skills.
Human-in-the-Loop AI Workflows: Approval Gates That Keep Agents Safe and Trusted
How to design human-in-the-loop into agent workflows — when to require approval, gate patterns, confidence escalation, review UX, and feedback loops.
Spec-Driven Development with AI Agents
Write the spec, let the agent implement against it — the SDD workflow (spec → plan → tasks → implement), when it beats prompt-and-iterate, and the tooling.
Amp
Sourcegraph's agentic coding tool — a CLI and editor extensions tuned for frontier-model coding.
Bolt
StackBlitz's in-browser AI agent that builds, runs, and deploys full-stack web apps in a WebContainer.
Claude Agent SDK
A toolkit for building custom agents on the same harness that powers Claude Code.
Claude Code
Anthropic’s official agentic coding tool that runs in the terminal, IDE, and web.
Devin
Cognition's autonomous AI software engineer that works in its own cloud workspace with an editor, terminal, and browser.
DSPy
Program language models instead of prompting them: declare tasks as typed signatures and let optimizers compile the prompts and few-shot examples for you.
Goose
Block's open-source, on-machine AI agent that is MCP-native and model-agnostic, with a CLI and desktop app.
Spec Kit
GitHub's open-source toolkit for spec-driven development — a specify CLI and /speckit slash commands that walk any coding agent from spec to implementation.
Warp
A modern, AI-powered terminal with an agent mode that can run and chain commands across your codebase.
Add Docstrings
Add or improve docstrings for the public API of a file or symbol.
Explain Code
Explain what the given code does, in clear prose with a short summary.
Update README
Update the README to reflect the current scripts, structure, and features of the repo.
Sync Branch
Fetch and rebase the current branch onto its base, resolving conflicts and verifying the build.
Breakdown Task
Decompose a task into an ordered checklist of small, verifiable steps.
Estimate Effort
Produce a grounded effort and complexity estimate for a task by exploring the codebase read-only.
Plan Feature
Explore the codebase and produce an implementation plan for a feature.
Write Design Doc
Explore the codebase and write a decision-oriented design doc / RFC for a feature or system change.
Create Skill
Scaffold a new Claude Code skill into .claude/skills/<name>/SKILL.md — a model-invoked capability with a trigger-rich description, scoped tools, and a lean body that pushes detail into resource files.
Create Slash Command
Scaffold a new Claude Code slash command into .claude/commands/ — a valid Markdown file with frontmatter, a least-privilege allowed-tools allowlist, and a $ARGUMENTS-driven body of numbered steps ending in a Report.
Create Subagent
Scaffold a new Claude Code subagent definition file into .claude/agents/ with a routing-ready description, scoped tools, and a system prompt.
Setup Claude CI
Wire Claude Code into this repo's CI the safe way — install the GitHub App or scaffold the workflow YAML, scope permissions to the minimum, set secrets correctly, and verify with a real trigger.
Agent Skills
Agent Skills are reusable procedures packaged as folders with a SKILL.md file — loaded by an AI agent on demand when a task matches, now an open standard.
AI Slop
AI slop is low-effort, mass-produced AI-generated content — fluent, generic, and unchecked — flooding feeds, search results, and codebases.
Chain-of-Thought (CoT)
Chain-of-thought prompting has a model work through intermediate reasoning steps before answering — improving accuracy on multi-step problems.
Context Engineering
Context engineering is the discipline of curating exactly what enters an LLM's context window so it has the right information and nothing else.
Extended Thinking
Extended thinking is the reasoning tokens a model generates before its final answer, trading latency and cost for higher accuracy on hard problems.
Few-Shot Prompting
Few-shot prompting includes worked examples in the prompt so the model learns the task's pattern from demonstrations instead of instructions alone.
Prompt Engineering
Prompt engineering is the practice of designing an LLM's inputs — instructions, context, examples, and format — to reliably get the output you want.
Prompt Template
A prompt template is a parameterized prompt — fixed instructions with variable slots — turning prompts from strings into versioned, testable components.
Subagent
A subagent is a specialist agent a primary agent delegates to — running in its own context window with its own prompt and tools, returning only a summary.
System Prompt
The system prompt is the standing instruction layer an LLM receives before user input — defining its role, rules, tools, and tone for the whole conversation.
Top-k Sampling
Top-k sampling restricts an LLM's next-token choice to the k most probable tokens before sampling; lower k is more deterministic, higher k more diverse.
Tree of Thoughts
Tree of Thoughts is a prompting method that explores multiple reasoning branches as a search tree, evaluating and backtracking among them.
Vibe Coding
Vibe coding is building software by describing intent in natural language and letting an AI agent write the code, judging results by behavior.
Zero-Shot Prompting
Zero-shot prompting asks a model to perform a task from instructions alone, with no examples — the default mode for capable modern LLMs.