Senior Prompt Engineer
maslennikov-ig/claude-code-orchestrator-kit
Provides reference guides and Python scripts for prompt optimization, RAG evaluation, and agent orchestration when building or tuning LLM systems.
Comprehensive guide for creating Claude Code agents with proper structure, triggering conditions, system prompts, and validation - combines official Anthropic best practices with proven patterns
$ npx skills add NeoLabHQ/context-engineering-kit --skill create-agent -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NeoLabHQ/context-engineering-kit create-agent --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/create-agent .claude/skills/create-agent && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "create-agent" agent skill from https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/create-agent into .claude/skills/create-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-agent", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/create-agentType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add NeoLabHQ/context-engineering-kit --skill create-agent -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NeoLabHQ/context-engineering-kit create-agent --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/create-agent .agents/skills/create-agent && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "create-agent" agent skill from https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/create-agent into .agents/skills/create-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-agent", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NeoLabHQ/context-engineering-kit --skill create-agent -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NeoLabHQ/context-engineering-kit create-agent --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/create-agent .cursor/skills/create-agent && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "create-agent" agent skill from https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/create-agent into .cursor/skills/create-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-agent", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/NeoLabHQ/context-engineering-kit.git --path skills/create-agent--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add NeoLabHQ/context-engineering-kit --skill create-agent -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NeoLabHQ/context-engineering-kit create-agent --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/create-agent .gemini/skills/create-agent && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "create-agent" agent skill from https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/create-agent into .gemini/skills/create-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-agent", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install NeoLabHQ/context-engineering-kit create-agentInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add NeoLabHQ/context-engineering-kit --skill create-agent -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kit.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/create-agent .github/skills/create-agent && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "create-agent" agent skill from https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/create-agent into .github/skills/create-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-agent", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NeoLabHQ/context-engineering-kit --skill create-agent -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install NeoLabHQ/context-engineering-kit create-agent --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/create-agent .opencode/skills/create-agent && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "create-agent" agent skill from https://github.com/NeoLabHQ/context-engineering-kit/tree/master/skills/create-agent into .opencode/skills/create-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-agent", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
create-agentComprehensive guide for creating Claude Code agents with proper structure, triggering conditions, system prompts, and validation - combines official Anthropic best practices with proven patterns
Create Agent is an agent skill from NeoLabHQ/context-engineering-kit. Comprehensive guide for creating Claude Code agents with proper structure, triggering conditions, system prompts, and validation - combines official Anthropic best practices with proven patterns
Its SKILL.md is about 5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering Building AI agents and Prompt engineering. The repository describes itself as: Hand-crafted Claude Code Skills focused on improving agent results quality. Compatible with OpenCode, Cursor, Antigravity, Gemini CLI, and others. Includes CodeRabbit open-source… The licence is GPL-3.0.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 23e2428. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown, bash and yaml).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Create Agent loads about 5k tokens when it runs. Until then it costs about 52 tokens; SKILL.md has 1,259 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from NeoLabHQ/context-engineering-kit at commit 23e2428, republished under its GPL-3.0 licence (© NeoLabHQ). 1,259 words, ~5,025 tokens.
.claude/skills/create-agent/SKILL.md (or your agent's skills folder).Create autonomous Claude Code agents that handle complex, multi-step tasks independently. This command provides comprehensive guidance based on official Anthropic documentation and proven patterns.
Agent Name: $1
Description: $2Agents are autonomous subprocesses spawned via the Task tool that:
| Concept | Agent | Command |
|---|---|---|
| Trigger | Claude decides based on description | User invokes with /name |
| Purpose | Autonomous work | User-initiated actions |
| Context | Isolated subprocess | Shared conversation |
| File format | agents/*.md | commands/*.md |
Agents use a unique format combining YAML frontmatter with a markdown system prompt:
---
name: agent-identifier
description: Use this agent when [triggering conditions]. Examples:
<example>
Context: [Situation description]
user: "[User request]"
assistant: "[How assistant should respond and use this agent]"
<commentary>
[Why this agent should be triggered]
</commentary>
</example>
<example>
[Additional example...]
</example>
model: inherit
color: blue
tools: ["Read", "Write", "Grep"]
---
You are [agent role description]...
**Your Core Responsibilities:**
1. [Responsibility 1]
2. [Responsibility 2]
**Analysis Process:**
[Step-by-step workflow]
**Output Format:**
[What to return]name (Required)Format: Lowercase with hyphens only Length: 3-50 characters Rules:
| Valid | Invalid | Reason |
|---|---|---|
code-reviewer | helper | Too generic |
test-generator | -agent- | Starts/ends with hyphen |
api-docs-writer | my_agent | Underscores not allowed |
security-analyzer | ag | Too short (<3 chars) |
pr-quality-reviewer | MyAgent | Uppercase not allowed |
description (Required, Critical)The most important field - Defines when Claude triggers the agent.
Requirements:
<example> blocks showing usage patternsExample Block Format:
<example>
Context: [Describe the situation - what led to this interaction]
user: "[Exact user message or request]"
assistant: "[How Claude should respond before triggering]"
<commentary>
[Explanation of why this agent should be triggered in this scenario]
</commentary>
assistant: "[How Claude triggers the agent - 'I'll use the [agent-name] agent...']"
</example>Best Practices for Descriptions:
model (Required)Values: inherit, sonnet, opus, haiku
Default: inherit (recommended)
| Value | Use Case | Cost |
|---|---|---|
inherit | Use parent conversation model | Default |
haiku | Fast, simple tasks | Lowest |
sonnet | Balanced performance | Medium |
opus | Maximum capability, complex reasoning | Highest |
Recommendation: Use inherit unless you have a specific reason to override.
color (Required)Purpose: Visual indicator in UI to distinguish agents
Values: blue, cyan, green, yellow, magenta, red
Best Practice: Use different colors for different agents in the same plugin to distinguish them visually.
tools (Optional)Purpose: Restrict available tools (principle of least privilege) Format: Array of tool names Default: All tools available
# Common tool restrictions
tools: ["Read", "Grep", "Glob"] # Read-only analysis
tools: ["Read", "Write", "Grep", "Glob"] # Code modification
tools: ["Read", "Bash", "Grep"] # System operationsSecurity Principle: Only grant tools the agent actually needs.
User directly asks for the agent's function.
<example>
Context: User wants code reviewed
user: "Can you review my code changes?"
assistant: "I'll use the code-reviewer agent to analyze the changes."
<commentary>
User explicitly requested code review, trigger the code-reviewer agent.
</commentary>
</example>Agent needed based on context, not explicit request.
<example>
Context: User mentions code is hard to understand
user: "This code is confusing and hard to follow"
assistant: "I can help improve the code clarity."
<commentary>
User indicates complexity issues. Trigger code-simplifier agent to refactor
for better readability.
</commentary>
assistant: "I'll use the code-simplifier agent to suggest improvements."
</example>Agent triggers after completing relevant work without explicit request.
<example>
Context: User just implemented database queries
user: "I've added the user search functionality"
assistant: "Great! Let me review it for security."
<commentary>
Database code written. Proactively trigger security-analyzer to check
for SQL injection and other database security issues.
</commentary>
assistant: "I'll use the security-analyzer agent to check the database code."
</example>Agent triggers based on prior tool usage.
<example>
Context: User made multiple edits to test files
user: "I've updated all the tests"
assistant: "Great! Let me verify test quality."
<commentary>
Multiple Edit tools used on test files. Proactively trigger test-quality-analyzer
to ensure tests follow best practices.
</commentary>
assistant: "I'll use the test-quality-analyzer agent to review the tests."
</example>The system prompt (markdown body after frontmatter) defines agent behavior. Use this proven template:
You are [role] specializing in [domain].
**Your Core Responsibilities:**
1. [Primary responsibility - what the agent MUST do]
2. [Secondary responsibility]
3. [Additional responsibilities...]
**Analysis Process:**
1. [Step one - be specific]
2. [Step two]
3. [Step three]
[...]
**Quality Standards:**
- [Standard 1 - measurable criteria]
- [Standard 2]
**Output Format:**
Provide results in this format:
- [What to include]
- [How to structure]
**Edge Cases:**
Handle these situations:
- [Edge case 1]: [How to handle]
- [Edge case 2]: [How to handle]
**What NOT to Do:**
- [Anti-pattern 1]
- [Anti-pattern 2]| Principle | Good | Bad |
|---|---|---|
| Be specific | "Check for SQL injection in query strings" | "Look for security issues" |
| Include examples | "Format: ## Critical Issues\n- Issue 1" | "Use proper formatting" |
| Define boundaries | "Do NOT modify files, only analyze" | No boundaries stated |
| Provide fallbacks | "If unsure, ask for clarification" | Assume and proceed |
| Quality mechanisms | "Verify each finding with evidence" | No verification |
System prompts must be:
Use this prompt to generate agent configurations automatically:
Create an agent configuration based on this request: "[YOUR DESCRIPTION]"
Requirements:
1. Extract core intent and responsibilities
2. Design expert persona for the domain
3. Create comprehensive system prompt with:
- Clear behavioral boundaries
- Specific methodologies
- Edge case handling
- Output format
4. Create identifier (lowercase, hyphens, 3-50 chars)
5. Write description with triggering conditions
6. Include 2-3 <example> blocks showing when to use
Return JSON with:
{
"identifier": "agent-name",
"whenToUse": "Use this agent when... Examples: <example>...</example>",
"systemPrompt": "You are..."
}When creating agents, follow this 6-step process:
description: Keep to ONE sentence - descriptions load into parent context, every token counts<example> blocks in description - they waste context tokens# <Role Title> with strong identity statementWRONG: Decompose → Self-Critique → Produce → Solve
RIGHT: Decompose → Solve → Produce Full Solution → Self-Critique → OutputPut reasoning column BEFORE decision column:
WRONG: | Section | Include? | Reasoning |
RIGHT: | Section | Reasoning | Include? |This forces the agent to explain WHY before deciding, improving decision quality.
| Component | Rule | Valid | Invalid |
|---|---|---|---|
| Name | 3-50 chars, lowercase, hyphens | code-reviewer | Code_Reviewer |
| Description | 10-5000 chars, starts "Use this agent when" | Use this agent when reviewing code... | Reviews code |
| Model | One of: inherit, sonnet, opus, haiku | inherit | gpt-4 |
| Color | One of: blue, cyan, green, yellow, magenta, red | blue | purple |
| System prompt | 20-10000 chars | 500+ char prompt | Empty body |
| Examples | At least one <example> block | Has examples | No examples |
# Validate agent structure
scripts/validate-agent.sh agents/your-agent.mdBefore deployment:
<example> blocks---
name: code-quality-reviewer
description: Use this agent when the user asks to review code changes, check code quality, or analyze modifications for bugs and improvements. Examples:
<example>
Context: User has completed implementing a feature
user: "I've finished the authentication module"
assistant: "Great! Let me review it for quality."
<commentary>
Code implementation complete. Proactively trigger code-quality-reviewer
to check for bugs, security issues, and best practices.
</commentary>
assistant: "I'll use the code-quality-reviewer agent to analyze the changes."
</example>
<example>
Context: User explicitly requests review
user: "Can you review PR #123 for code quality?"
assistant: "I'll use the code-quality-reviewer agent to analyze the PR."
<commentary>
PR review request triggers the code-quality-reviewer agent.
</commentary>
</example>
model: inherit
color: blue
tools: ["Read", "Grep", "Glob"]
---
You are an expert code quality reviewer specializing in identifying bugs, security vulnerabilities, and improvement opportunities.
**Your Core Responsibilities:**
1. Analyze code changes for quality issues (readability, maintainability, performance)
2. Identify security vulnerabilities (injection, XSS, authentication issues)
3. Check adherence to project best practices and coding standards
4. Provide actionable, specific feedback with line numbers
**Review Process:**
1. **Initial scan**: Quick pass for obvious issues
2. **Deep analysis**: Line-by-line review of changed code
3. **Context evaluation**: Check impact on related code
4. **Best practices**: Compare against project and language standards
5. **Recommendations**: Prioritized list of improvements
**Output Format:**
For each file reviewed:
## Summary
[2-3 sentence overview]
## Critical Issues (must fix)
- [Issue with file:line reference and fix suggestion]
## Major Issues (should fix)
- [Issue with explanation]
## Minor Issues (nice to fix)
- [Suggestion]
## Positive Observations
- [What was done well]
## Overall Assessment
[Pass/Needs Work/Fail with reasoning]
**Quality Standards:**
- Every issue must have a specific location (file:line)
- Every issue must have a suggested fix
- Prioritize security over style issues
- Acknowledge good patterns, not just problems---
name: test-generator
description: Use this agent when the user asks for test generation, needs test coverage, or has written new code requiring tests. Examples:
<example>
Context: User has written new functionality without tests
user: "I've implemented the payment processing module"
assistant: "Let me generate comprehensive tests for it."
<commentary>
New code written without tests. Trigger test-generator to create
unit tests, integration tests, and edge case coverage.
</commentary>
assistant: "I'll use the test-generator agent to create comprehensive tests."
</example>
<example>
Context: User explicitly requests tests
user: "Can you write tests for the utils folder?"
assistant: "I'll use the test-generator agent to create tests."
<commentary>
Explicit test generation request.
</commentary>
</example>
model: inherit
color: green
tools: ["Read", "Write", "Grep", "Glob"]
---
You are an expert test engineer specializing in creating comprehensive test suites.
**Your Core Responsibilities:**
1. Analyze code to understand behavior and dependencies
2. Generate unit tests for individual functions/methods
3. Create integration tests for module interactions
4. Design edge case and error condition tests
5. Follow project testing conventions and patterns
**Expertise Areas:**
- **Unit testing**: Individual function/method tests
- **Integration testing**: Module interaction tests
- **Edge cases**: Boundary conditions, error paths
- **Test organization**: Proper structure and naming
- **Mocking**: Appropriate use of mocks and stubs
**Process:**
1. Read target code and understand its behavior
2. Identify testable units and their dependencies
3. Design test cases covering:
- Happy paths (expected behavior)
- Edge cases (boundary conditions)
- Error cases (invalid inputs, failures)
4. Generate tests following project patterns
5. Add comprehensive assertions
**Output Format:**
Complete test files with:
- Proper test suite structure (describe/it or test blocks)
- Setup/teardown if needed
- Descriptive test names explaining what's being tested
- Comprehensive assertions covering all behaviors
- Comments explaining complex test logic
**Quality Standards:**
- Each function should have at least 3 tests (happy, edge, error)
- Test names should describe the scenario being tested
- Mocks should be clearly documented
- No test interdependenciesAsk user (if not provided):
# Create agents directory if needed
mkdir -p ${CLAUDE_PLUGIN_ROOT}/agents
# Create agent file
touch ${CLAUDE_PLUGIN_ROOT}/agents/<agent-name>.mdGenerate frontmatter with:
Create system prompt following the template:
Run validation:
scripts/validate-agent.sh agents/<agent-name>.mdCheck:
Test with various scenarios:
Agents integrate with plugin workflows:
For comprehensive plugin development, use:
/plugin-dev:create-plugin for full plugin workflowBased on user input, create:
${CLAUDE_PLUGIN_ROOT}/agents/After creation, suggest testing with /customaize-agent:test-prompt command to verify agent behavior under various scenarios.
© NeoLabHQ, GPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/create-agent of NeoLabHQ/context-engineering-kit.
Open the folder on GitHubat commit 23e2428
Create Agent next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Create Agent this skillNeoLabHQ/context-engineering-kit | 1.7k | — | ~5k | Automated safety check: Pass | GPL-3.0 | |
| Senior Prompt Engineermaslennikov-ig/claude-code-orchestrator-kit | 260 | 4 repos | ~1.4k | Automated safety check: Pass | Custom licence | |
| Create System Promptpnp/copilot-prompts | 892 | — | ~3.1k | Automated safety check: Pass | MIT | |
| DSPy Language Model ProgrammingOrchestra-Research/AI-Research-SKILLs | 13k | 10 repos | ~3.8k | Automated safety check: Pass | MIT | |
| Building Agent Systemstelagod/code-abyss | 243 | — | ~691 | Automated safety check: Pass | MIT | |
| Agentsop Dspyagentsope/SkillAlchemy | 459 | — | ~7k | Automated safety check: Pass | MIT |
maslennikov-ig/claude-code-orchestrator-kit
Provides reference guides and Python scripts for prompt optimization, RAG evaluation, and agent orchestration when building or tuning LLM systems.
pnp/copilot-prompts
This skill should be used when the user asks to "create an agent instruction", "add agent instructions", "scaffold an agent sample", "create a system prompt sample", "add a system prompt", "create a…
Orchestra-Research/AI-Research-SKILLs
Teaches an agent to build LM pipelines, RAG systems and agents in DSPy using signatures, modules and optimizers instead of hand-tuned prompts.
telagod/code-abyss
AI agent and LLM system engineering reference covering single-agent dev (ReAct, tool calling, plan-execute), multi-agent coordination (swarm, role decomposition, file locking), LLM security (prompt…
agentsope/SkillAlchemy
Operating SOP for DSPy (Stanford NLP) — the declarative framework for "programming, not prompting" language models.
aiskillstore/marketplace
Creates specialized AI agents with optimized system prompts using the official 4-phase SOP methodology from Desktop .claude-flow, combined with evidence-based prompting techniques and Claude Agent…
NeoLabHQ/context-engineering-kit
A skill your agent uses when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing…
NeoLabHQ/context-engineering-kit
A skill your agent uses when adding metadata to commits without changing history, tracking review status, test results, code quality annotations, or supplementing commit messages post-hoc - provides…
NeoLabHQ/context-engineering-kit
Design multi-agent architectures for complex tasks. An agent skill from NeoLabHQ/context-engineering-kit.
NeoLabHQ/context-engineering-kit
A skill your agent uses to load open/unresolved PR review comments then aggregate them as tasks in .specs/comments/.md for parallel agents to fix.
NeoLabHQ/context-engineering-kit
Review an existing GitHub pull request and post inline review comments on its diff.
NeoLabHQ/context-engineering-kit
A skill your agent uses when executing implementation plans with independent tasks in the current session or facing 3+ independent issues that can be investigated without shared state or…
Categories
Comprehensive guide for creating Claude Code agents with proper structure, triggering conditions, system prompts, and validation - combines official Anthropic best practices with proven patterns. Create Agent is an agent skill from NeoLabHQ/context-engineering-kit.
Create Agent fits situations like: tasks that involve Building AI agents; tasks that involve Prompt engineering.
Run `npx skills add NeoLabHQ/context-engineering-kit --skill create-agent -a claude-code`. Or copy the skill folder (skills/create-agent in NeoLabHQ/context-engineering-kit) into .claude/skills/create-agent in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NeoLabHQ/context-engineering-kit --skill create-agent -a codex`. Or copy the skill folder (skills/create-agent in NeoLabHQ/context-engineering-kit) into .agents/skills/create-agent in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NeoLabHQ/context-engineering-kit --skill create-agent -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/create-agent, .gemini/skills/create-agent, .github/skills/create-agent and .opencode/skills/create-agent in your project.
SKILL.md names no scripts, command-line tools or credentials: Create Agent is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Create Agent is published under the GPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 5k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Create Agent: Senior Prompt Engineer (maslennikov-ig/claude-code-orchestrator-kit, 260 stars), Create System Prompt (pnp/copilot-prompts, 892 stars), DSPy Language Model Programming (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Building Agent Systems (telagod/code-abyss, 243 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
NeoLabHQ (a GitHub organization) maintains it in NeoLabHQ/context-engineering-kit, which has 1,748 GitHub stars. The repository holds 57 skills in this directory. The repository was last updated on August 26, 2026.
Source: NeoLabHQ/context-engineering-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.