Agent skill

Building Agents Core

by majiayu000 in majiayu000/claude-skill-registry

Core concepts for goal-driven agents - architecture, node types, tool discovery, and workflow overview.

Apache-2.0Auto-check passedAI & LLM Engineering

Install Building Agents Core

skills CLI

$ npx skills add majiayu000/claude-skill-registry --skill building-agents-core -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry building-agents-core --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/agent/building-agents-core .claude/skills/building-agents-core && rm -rf skills-src

Use ~/.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/

Paste into Claude Code

Install the "building-agents-core" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/agent/building-agents-core into .claude/skills/building-agents-core/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "building-agents-core", 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

$skill-installer install https://github.com/majiayu000/claude-skill-registry/tree/main/skills/agent/building-agents-core

Type 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.

skills CLI

$ npx skills add majiayu000/claude-skill-registry --skill building-agents-core -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry building-agents-core --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/agent/building-agents-core .agents/skills/building-agents-core && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "building-agents-core" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/agent/building-agents-core into .agents/skills/building-agents-core/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "building-agents-core", 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.

skills CLI

$ npx skills add majiayu000/claude-skill-registry --skill building-agents-core -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry building-agents-core --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/agent/building-agents-core .cursor/skills/building-agents-core && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "building-agents-core" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/agent/building-agents-core into .cursor/skills/building-agents-core/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "building-agents-core", 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

$ gemini skills install https://github.com/majiayu000/claude-skill-registry.git --path skills/agent/building-agents-core

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add majiayu000/claude-skill-registry --skill building-agents-core -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry building-agents-core --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/agent/building-agents-core .gemini/skills/building-agents-core && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "building-agents-core" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/agent/building-agents-core into .gemini/skills/building-agents-core/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "building-agents-core", 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.

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry building-agents-core

Installs 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).

skills CLI

$ npx skills add majiayu000/claude-skill-registry --skill building-agents-core -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/agent/building-agents-core .github/skills/building-agents-core && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "building-agents-core" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/agent/building-agents-core into .github/skills/building-agents-core/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "building-agents-core", 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.

skills CLI

$ npx skills add majiayu000/claude-skill-registry --skill building-agents-core -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry building-agents-core --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/agent/building-agents-core .opencode/skills/building-agents-core && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "building-agents-core" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/agent/building-agents-core into .opencode/skills/building-agents-core/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "building-agents-core", 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.

Facts

Skill name: building-agents-core
GitHub stars: 666
Used in: 1 other repo
Token cost: ~2.1k tokens
SKILL.md length: 459 words
Files: 2
Skills in repo: 1,273
Repo updated: Oct 7, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Core concepts for goal-driven agents - architecture, node types, tool discovery, and workflow overview.

Works in 3 steps: Register MCP Server (if not already done) → Discover Available Tools → Validate Before Adding Nodes
Starting agent development
SKILL.md covers Architecture: Python Services…, Core Concepts, Tool Discovery & Validation and Workflow Overview: Incremental…, plus 3 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Building Agents Core is an agent skill from majiayu000/claude-skill-registry. Core concepts for goal-driven agents - architecture, node types, tool discovery, and workflow overview. Use when starting agent development or need to understand agent fundamentals.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).

It sits in AI & LLM Engineering, covering Building AI agents and MCP servers. It works with Python. The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is Apache-2.0.

When your agent uses it

Starting agent development
Need to understand agent fundamentals

Example prompts

“/building-agents-core”

Requirements

Python 3

Workflow steps

3 steps, taken from the step headings in SKILL.md.

Register MCP Server (if not already done)
Discover Available Tools
Validate Before Adding Nodes

What it can do on your machine

Read from SKILL.md and the folder at commit 2d14a69. It shows what the files ask for, not the result of running them.

Tool permissions
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.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python and json).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Building Agents Core loads about 2.1k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 459 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~51
When it runs · the whole SKILL.md, loaded when a task matches: ~2.1k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from majiayu000/claude-skill-registry at commit 2d14a69, republished under its Apache-2.0 licence (© majiayu000). 459 words, ~2,085 tokens.

Download SKILL.mdSave it as .claude/skills/building-agents-core/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: building-agents-core
description: Core concepts for goal-driven agents - architecture, node types, tool discovery, and workflow overview. Use when starting agent development or need to understand agent fundamentals.
license: Apache-2.0
metadata.author: hive
metadata.version: 1.0
metadata.type: foundational
metadata.part_of: building-agents

Building Agents - Core Concepts

Foundational knowledge for building goal-driven agents as Python packages.

Architecture: Python Services (Not JSON Configs)

Agents are built as Python packages:

exports/my_agent/
├── __init__.py          # Package exports
├── __main__.py          # CLI (run, info, validate, shell)
├── agent.py             # Graph construction (goal, edges, agent class)
├── nodes/__init__.py    # Node definitions (NodeSpec)
├── config.py            # Runtime config
└── README.md            # Documentation

Key Principle: Agent is visible and editable during build

✅ Files created immediately as components are approved
✅ User can watch files grow in their editor
✅ No session state - just direct file writes
✅ No "export" step - agent is ready when build completes

Core Concepts

Goal

Success criteria and constraints (written to agent.py)

python

goal = Goal(
    id="research-goal",
    name="Technical Research Agent",
    description="Research technical topics thoroughly",
    success_criteria=[
        SuccessCriterion(
            id="completeness",
            description="Cover all aspects of topic",
            metric="coverage_score",
            target=">=0.9",
            weight=0.4,
        ),
        # 3-5 success criteria total
    ],
    constraints=[
        Constraint(
            id="accuracy",
            description="All information must be verified",
            constraint_type="hard",
            category="quality",
        ),
        # 1-5 constraints total
    ],
)

Node

Unit of work (written to nodes/init.py)

Node Types:

llm_generate - Text generation, parsing
llm_tool_use - Actions requiring tools
router - Conditional branching
function - Deterministic operations

python

search_node = NodeSpec(
    id="search-web",
    name="Search Web",
    description="Search for information online",
    node_type="llm_tool_use",
    input_keys=["query"],
    output_keys=["search_results"],
    system_prompt="Search the web for: {query}",
    tools=["web_search"],
    max_retries=3,
)

Edge

Connection between nodes (written to agent.py)

Edge Conditions:

on_success - Proceed if node succeeds
on_failure - Handle errors
always - Always proceed
conditional - Based on expression

python

EdgeSpec(
    id="search-to-analyze",
    source="search-web",
    target="analyze-results",
    condition=EdgeCondition.ON_SUCCESS,
    priority=1,
)

Pause/Resume

Multi-turn conversations

Pause nodes - Stop execution, wait for user input
Resume entry points - Continue from pause with user's response

python

# Example pause/resume configuration
pause_nodes = ["request-clarification"]
entry_points = {
    "start": "analyze-request",
    "request-clarification_resume": "process-clarification"
}

Tool Discovery & Validation

CRITICAL: Before adding a node with tools, you MUST verify the tools exist.

Tools are provided by MCP servers. Never assume a tool exists - always discover dynamically.

Step 1: Register MCP Server (if not already done)

python

mcp__agent-builder__add_mcp_server(
    name="tools",
    transport="stdio",
    command="python",
    args='["mcp_server.py", "--stdio"]',
    cwd="../tools"
)

Step 2: Discover Available Tools

python

# List all tools from all registered servers
mcp__agent-builder__list_mcp_tools()

# Or list tools from a specific server
mcp__agent-builder__list_mcp_tools(server_name="tools")

This returns available tools with their descriptions and parameters:

json

{
  "success": true,
  "tools_by_server": {
    "tools": [
      {
        "name": "web_search",
        "description": "Search the web...",
        "parameters": ["query"]
      },
      {
        "name": "web_scrape",
        "description": "Scrape a URL...",
        "parameters": ["url"]
      }
    ]
  },
  "total_tools": 14
}

Step 3: Validate Before Adding Nodes

Before writing a node with tools=[...]:

Call list_mcp_tools() to get available tools
Check each tool in your node exists in the response
If a tool doesn't exist:
- DO NOT proceed with the node
- Inform the user: "The tool 'X' is not available. Available tools are: ..."
- Ask if they want to use an alternative or proceed without the tool

Show full SKILL.md (197 more words)Show less

Tool Validation Anti-Patterns

❌ Never assume a tool exists - always call list_mcp_tools() first ❌ Never write a node with unverified tools - validate before writing ❌ Never silently drop tools - if a tool doesn't exist, inform the user ❌ Never guess tool names - use exact names from discovery response

Example Validation Flow

python

# 1. User requests: "Add a node that searches the web"
# 2. Discover available tools
tools_response = mcp__agent-builder__list_mcp_tools()

# 3. Check if web_search exists
available = [t["name"] for tools in tools_response["tools_by_server"].values() for t in tools]
if "web_search" not in available:
    # Inform user and ask how to proceed
    print("❌ 'web_search' not available. Available tools:", available)
else:
    # Proceed with node creation
    # ...

Workflow Overview: Incremental File Construction

1. CREATE PACKAGE → mkdir + write skeletons
2. DEFINE GOAL → Write to agent.py + config.py
3. FOR EACH NODE:
   - Propose design
   - User approves
   - Write to nodes/__init__.py IMMEDIATELY ← FILE WRITTEN
   - (Optional) Validate with test_node ← MCP VALIDATION
   - User can open file and see it
4. CONNECT EDGES → Update agent.py ← FILE WRITTEN
   - (Optional) Validate with validate_graph ← MCP VALIDATION
5. FINALIZE → Write agent class to agent.py ← FILE WRITTEN
6. DONE - Agent ready at exports/my_agent/

Files written immediately. MCP tools optional for validation/testing bookkeeping.

The Key Difference

OLD (Bad):

MCP add_node → Session State → MCP add_node → Session State → ...
                                                                ↓
                                                     MCP export_graph
                                                                ↓
                                                       Files appear

NEW (Good):

Write node to file → (Optional: MCP test_node) → Write node to file → ...
       ↓                                               ↓
  File visible                                    File visible
  immediately                                     immediately

Bottom line: Use Write/Edit for construction, MCP for validation if needed.

When to Use This Skill

Use building-agents-core when:

Starting a new agent project and need to understand fundamentals
Need to understand agent architecture before building
Want to validate tool availability before proceeding
Learning about node types, edges, and graph execution

Next Steps:

Ready to build? → Use building-agents-construction skill
Need patterns and examples? → Use building-agents-patterns skill

MCP Tools for Validation

After writing files, optionally use MCP tools for validation:

test_node - Validate node configuration with mock inputs

python

mcp__agent-builder__test_node(
    node_id="search-web",
    test_input='{"query": "test query"}',
    mock_llm_response='{"results": "mock output"}'
)

validate_graph - Check graph structure

python

mcp__agent-builder__validate_graph()
# Returns: unreachable nodes, missing connections, etc.

create_session - Track session state for bookkeeping

python

mcp__agent-builder__create_session(session_name="my-build")

Key Point: Files are written FIRST. MCP tools are for validation only.

building-agents-construction - Step-by-step building process
building-agents-patterns - Best practices and examples
agent-workflow - Complete workflow orchestrator
testing-agent - Test and validate completed agents

Files

SKILL.md and 1 other file in skills/agent/building-agents-core of majiayu000/claude-skill-registry.

SKILL.md
metadata.json

Open the folder on GitHubat commit 2d14a69

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 7, 2026.

NeverSight/learn-skills.devdata/skills-md/adenhq/hive/building-agents-core

Compare with similar skills

Building Agents Core 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.

Building Agents Core compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Building Agents Core this skillmajiayu000/claude-skill-registry	666	1 repos	~2.1k	Automated safety check: Pass	Apache-2.0	yesterday
Cloudbase Agent PythonTencentCloudBase/CloudBase-AI-Toolkit	1.1k	2 repos	~2.9k	Automated safety check: Notes	MIT	yesterday
Strandsstrands-agents/harness-sdk	8.7k	—	~1k	Automated safety check: Pass	Apache-2.0	today
Ydc Openai Agent SDK IntegrationLeoYeAI/openclaw-master-skills	2.2k	—	~4.4k	Automated safety check: Notes	MIT	2 mo ago
Synthetic Data GenerationRed-Hat-AI-Innovation-Team/sdg_hub	164	—	~3.1k	Automated safety check: Pass	Apache-2.0	yesterday
Tool Designagentailor/fullstack-langgraph-nextjs-agent	132	—	~3.2k	Automated safety check: Pass	MIT	1 mo ago

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Questions about Building Agents Core

What does Building Agents Core do?

Core concepts for goal-driven agents - architecture, node types, tool discovery, and workflow overview. Building Agents Core is an agent skill from majiayu000/claude-skill-registry. Core concepts for goal-driven agents - architecture, node types, tool discovery, and workflow overview.

When should I use Building Agents Core?

Building Agents Core fits situations like: starting agent development; need to understand agent fundamentals.

How do I install Building Agents Core in Claude Code?

Run `npx skills add majiayu000/claude-skill-registry --skill building-agents-core -a claude-code`. Or copy the skill folder (skills/agent/building-agents-core in majiayu000/claude-skill-registry) into .claude/skills/building-agents-core in your project. Claude Code loads it when a task matches its description.

How do I install Building Agents Core in Codex?

Run `npx skills add majiayu000/claude-skill-registry --skill building-agents-core -a codex`. Or copy the skill folder (skills/agent/building-agents-core in majiayu000/claude-skill-registry) into .agents/skills/building-agents-core in your project. Codex loads it when a task matches its description.

Can I use Building Agents Core in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/claude-skill-registry --skill building-agents-core -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/building-agents-core, .gemini/skills/building-agents-core, .github/skills/building-agents-core and .opencode/skills/building-agents-core in your project.

What does Building Agents Core need to run?

SKILL.md names no scripts, command-line tools or credentials: Building Agents Core is instructions for the agent only. Our summary lists: Python 3.

Does Building Agents Core access the network?

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.

Is Building Agents Core safe to install?

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.

What licence does Building Agents Core use?

Building Agents Core is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Building Agents Core use?

About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Building Agents Core?

Skills that share tags, products or a category with Building Agents Core: Cloudbase Agent Python (TencentCloudBase/CloudBase-AI-Toolkit, 1.1k stars), Strands (strands-agents/harness-sdk, 8.7k stars), Ydc Openai Agent SDK Integration (LeoYeAI/openclaw-master-skills, 2.2k stars) and Synthetic Data Generation (Red-Hat-AI-Innovation-Team/sdg_hub, 164 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Building Agents Core?

majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 1,273 skills in this directory. The repository was last updated on October 7, 2026.

Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Building Agents Core

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Building Agents - Core Concepts

Architecture: Python Services (Not JSON Configs)

Core Concepts

Goal

Node

Edge

Pause/Resume

Tool Discovery & Validation

Step 1: Register MCP Server (if not already done)

Step 2: Discover Available Tools

Step 3: Validate Before Adding Nodes

Tool Validation Anti-Patterns

Example Validation Flow

Workflow Overview: Incremental File Construction

The Key Difference

When to Use This Skill

MCP Tools for Validation

Related Skills

Files

Used in 1 other repository

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