Agent Tool Builder
omer-metin/skills-for-antigravity
Tools are how AI agents interact with the world. An agent skill from omer-metin/skills-for-antigravity.
Design AI agent communication protocols: MCP tool schemas, A2A, function calling, and inter- agent messaging.
Install Agent Protocol
$ npx skills add borghei/Claude-Skills --skill agent-protocol -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install borghei/Claude-Skills agent-protocol --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/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/engineering/agent-protocol .claude/skills/agent-protocol && 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 "agent-protocol" agent skill from https://github.com/borghei/Claude-Skills/tree/main/engineering/agent-protocol into .claude/skills/agent-protocol/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-protocol", 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/borghei/Claude-Skills/tree/main/engineering/agent-protocolType 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 borghei/Claude-Skills --skill agent-protocol -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install borghei/Claude-Skills agent-protocol --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/engineering/agent-protocol .agents/skills/agent-protocol && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "agent-protocol" agent skill from https://github.com/borghei/Claude-Skills/tree/main/engineering/agent-protocol into .agents/skills/agent-protocol/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-protocol", 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 borghei/Claude-Skills --skill agent-protocol -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install borghei/Claude-Skills agent-protocol --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/engineering/agent-protocol .cursor/skills/agent-protocol && 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 "agent-protocol" agent skill from https://github.com/borghei/Claude-Skills/tree/main/engineering/agent-protocol into .cursor/skills/agent-protocol/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-protocol", 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/borghei/Claude-Skills.git --path engineering/agent-protocol--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 borghei/Claude-Skills --skill agent-protocol -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install borghei/Claude-Skills agent-protocol --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/engineering/agent-protocol .gemini/skills/agent-protocol && 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 "agent-protocol" agent skill from https://github.com/borghei/Claude-Skills/tree/main/engineering/agent-protocol into .gemini/skills/agent-protocol/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-protocol", 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 borghei/Claude-Skills agent-protocolInstalls 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 borghei/Claude-Skills --skill agent-protocol -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/engineering/agent-protocol .github/skills/agent-protocol && 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 "agent-protocol" agent skill from https://github.com/borghei/Claude-Skills/tree/main/engineering/agent-protocol into .github/skills/agent-protocol/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-protocol", 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 borghei/Claude-Skills --skill agent-protocol -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install borghei/Claude-Skills agent-protocol --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/engineering/agent-protocol .opencode/skills/agent-protocol && 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 "agent-protocol" agent skill from https://github.com/borghei/Claude-Skills/tree/main/engineering/agent-protocol into .opencode/skills/agent-protocol/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-protocol", 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
agent-protocol- GitHub stars
- 881
- Token cost
- ~1.6k tokens
- SKILL.md length
- 627 words
- Files
- 8 (incl. scripts, references)
- Skills in repo
- 349
- Repo updated
- First seen
- Licence
- MIT
At a glance
Design AI agent communication protocols: MCP tool schemas, A2A, function calling, and inter- agent messaging.
- Building multi-agent systems
- SKILL.md covers Core Capabilities, When to Use, Clarify First and Decision Framework, plus 3 more sections
- Runs Python scripts from its folder
- Defining tool interfaces
What it does
Agent Protocol is an agent skill from borghei/Claude-Skills. Design AI agent communication protocols: MCP tool schemas, A2A, function calling, and inter- agent messaging. Use when building multi-agent systems, defining tool interfaces, or implementing agent-to-agent communication.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `references/a2a-and-bridges.md`, `references/errors-testing-and-quality.md` and `references/mcp-implementation.md`).
It sits in AI & LLM Engineering, covering Structured output and tool calling and MCP servers. It works with Model Context Protocol and OpenAI. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.
When your agent uses it
- Building multi-agent systems
- Defining tool interfaces
- Implementing agent-to-agent communication
Example prompts
- “/agent-protocol”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit 4a698e8. 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
Ships 3 files in scripts/ (Python), which the agent can run.
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
Agent Protocol loads about 1.6k tokens when it runs, and up to ~7.1k if it reads all its reference files. Until then it costs about 59 tokens; SKILL.md has 627 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.
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); the scripts in this folder are not scanned.
SKILL.md
The full file from borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 627 words, ~1,649 tokens.
Download SKILL.mdSave it as
.claude/skills/agent-protocol/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.- name
- agent-protocol
- description
- Design AI agent communication protocols: MCP tool schemas, A2A, function calling, and inter- agent messaging. Use when building multi-agent systems, defining tool interfaces, or implementing agent-to-agent communication.
- license
- MIT + Commons Clause
- metadata.version
- 1.1.0
- metadata.author
- borghei
- metadata.category
- engineering
- metadata.domain
- ai-agent-systems
- metadata.tier
- POWERFUL
- metadata.updated
- 2026-06-15
- metadata.frameworks
- mcp, a2a, openai-functions, langchain-tools
Agent Protocol
The agent designs tool schemas for MCP, Google A2A, and OpenAI Function Calling protocols. It implements transport selection, capability discovery, authentication flows (OAuth 2.1, API keys), structured error handling, rate limiting, and protocol bridges for heterogeneous agent ecosystems.
Core Capabilities
- Protocol selection & comparison — MCP (tool/resource/prompt serving), Google A2A (agent cards, task lifecycle, streaming), OpenAI Function Calling (JSON Schema, parallel calls, strict mode), LangChain/LangGraph tools, and custom WebSocket/gRPC messaging
- Tool schema design — JSON Schema input/output validation, semantic naming conventions, description engineering for LLM comprehension, required vs optional parameters, enum and default strategies
- Transport & discovery — stdio/SSE/WebSocket for MCP, HTTP+JSON-RPC for A2A, agent card capability advertisement, health checking, and protocol version negotiation
- Security & authentication — OAuth 2.1 flows, API key rotation and scoping, request signing, per-identity rate limiting, and audit logging for inter-agent calls
When to Use
- Designing tool interfaces for LLM-powered agents
- Building MCP servers that expose APIs to Claude, Cursor, or other clients
- Implementing agent-to-agent communication in multi-agent systems
- Bridging between different agent protocols (MCP to A2A, etc.)
- Standardizing tool calling patterns across a team or organization
- Debugging agent tool selection failures
Clarify First
Before designing the protocol, confirm these inputs. If any is unknown or vague, ASK — do not assume:
- Protocol target — MCP, A2A, OpenAI Function Calling, or LangChain Tools (drives the entire schema and transport design via the Decision Framework below)
- Transport & client — which client consumes it (stdio/SSE/WebSocket for MCP, HTTP+JSON-RPC for A2A)
- Auth & trust boundary — in-process vs cross-organization (determines OAuth 2.1 vs API key vs none, plus rate limiting and signing)
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
Decision Framework
What are you building?
│
├─ Tools for a single LLM client (Claude, Cursor, Copilot)
│ └─ Use MCP — it's the native protocol for tool serving
│
├─ Agent-to-agent communication across organizations
│ └─ Use A2A — designed for cross-boundary agent discovery and delegation
│
├─ Tools for OpenAI models specifically
│ └─ Use OpenAI Function Calling — tightest integration
│
├─ Python pipeline with multiple chained tools
│ └─ Use LangChain Tools — simplest for in-process orchestration
│
└─ Heterogeneous agent ecosystem (multiple protocols)
└─ Use Protocol Bridge pattern — translate between protocols at boundariesReferences
Load the reference that matches the task — keep this file lean and pull detail on demand:
- references/protocol-selection.md — full MCP vs A2A vs OpenAI Functions vs LangChain Tools comparison matrix. Read when comparing protocols before committing to one.
- references/mcp-implementation.md — tool schema anatomy, naming/description rules, and TypeScript MCP server code (stdio + authenticated SSE). Read when building an MCP server or designing tool schemas.
- references/a2a-and-bridges.md — A2A agent card, task lifecycle, full Python A2A client, and the Protocol Bridge pattern. Read when building agent-to-agent communication or bridging protocols.
- references/errors-testing-and-quality.md — structured error format, error code taxonomy, schema/integration testing, pitfalls, best practices, troubleshooting, and success criteria. Read when hardening for production or diagnosing failures.
Show full SKILL.md (233 more words)Show less
Scope & Limitations
This skill covers:
- Designing tool schemas for MCP, A2A, OpenAI Function Calling, and LangChain Tools
- Transport selection, capability discovery, and protocol version negotiation
- Authentication, rate limiting, and structured error handling for agent communication
- Protocol bridging between heterogeneous agent ecosystems
This skill does NOT cover:
- Building complete MCP server applications with business logic — see
engineering/mcp-server-builder - Agent orchestration patterns, planning loops, or multi-step reasoning — see
engineering/agent-workflow-designer - Designing agent personas, memory systems, or behavioral profiles — see
engineering/agent-designer - Infrastructure deployment, CI/CD pipelines, or container orchestration for agent services — see
engineering/senior-devops
Integration Points
| Skill | Integration | Data Flow |
|---|---|---|
engineering/mcp-server-builder | Protocol schemas defined here feed directly into MCP server scaffolding | Tool definitions and inputSchema objects flow into server code generation |
engineering/agent-workflow-designer | Workflow orchestrators consume protocol interfaces to dispatch tasks | Agent-protocol defines the transport contract; workflow-designer defines execution order and branching |
engineering/agent-designer | Agent identity and capability profiles reference protocol-level skill declarations | Agent cards and capability metadata from protocol design inform agent persona configuration |
engineering/senior-security | Security review of auth flows, token scoping, and rate limiting configurations | OAuth 2.1 flows, API key rotation policies, and audit logging patterns flow into security assessments |
engineering/api-design-reviewer | REST and JSON-RPC endpoint design review for A2A and MCP HTTP transports | API schema and endpoint contracts feed into design review checklists |
engineering/observability-designer | Monitoring and tracing for inter-agent calls, latency tracking, and error budgets | Tool call logs with agent ID, latency, and error codes flow into observability dashboards |
© borghei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 7 other files (scripts, references) in engineering/agent-protocol of borghei/Claude-Skills.
- SKILL.md
- references/a2a-and-bridges.md
- references/errors-testing-and-quality.md
- references/mcp-implementation.md
- references/protocol-selection.md
- scripts/capability_mapper.py
- scripts/protocol_validator.py
- scripts/schema_generator.py
Open the folder on GitHubat commit 4a698e8
Compare with similar skills
Agent Protocol 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 |
|---|---|---|---|---|---|---|
| Agent Protocol this skillborghei/Claude-Skills | 881 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Agent Tool Builderomer-metin/skills-for-antigravity | 162 | — | ~705 | Automated safety check: Pass | Apache-2.0 | |
| Tool Designagentailor/fullstack-langgraph-nextjs-agent | 132 | — | ~3.2k | Automated safety check: Pass | MIT | |
| Local AI Agentsmicrosoft/ai-agents-for-beginners | 77k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Local AI Agentsmicrosoft/ai-agents-for-beginners | 77k | — | ~1.4k | Automated safety check: Pass | MIT | |
| Local AI Agentsmicrosoft/ai-agents-for-beginners | 77k | — | ~1.7k | Automated safety check: Pass | MIT |
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Questions about Agent Protocol
What does Agent Protocol do?
Design AI agent communication protocols: MCP tool schemas, A2A, function calling, and inter- agent messaging. Agent Protocol is an agent skill from borghei/Claude-Skills. Design AI agent communication protocols: MCP tool schemas, A2A, function calling, and inter- agent messaging.
When should I use Agent Protocol?
Agent Protocol fits situations like: building multi-agent systems; defining tool interfaces; implementing agent-to-agent communication.
How do I install Agent Protocol in Claude Code?
Run `npx skills add borghei/Claude-Skills --skill agent-protocol -a claude-code`. Or copy the skill folder (engineering/agent-protocol in borghei/Claude-Skills) into .claude/skills/agent-protocol in your project. Claude Code loads it when a task matches its description.
How do I install Agent Protocol in Codex?
Run `npx skills add borghei/Claude-Skills --skill agent-protocol -a codex`. Or copy the skill folder (engineering/agent-protocol in borghei/Claude-Skills) into .agents/skills/agent-protocol in your project. Codex loads it when a task matches its description.
Can I use Agent Protocol 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 borghei/Claude-Skills --skill agent-protocol -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-protocol, .gemini/skills/agent-protocol, .github/skills/agent-protocol and .opencode/skills/agent-protocol in your project.
What does Agent Protocol need to run?
Going by SKILL.md and its folder, Agent Protocol needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Agent Protocol 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 Agent Protocol 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Agent Protocol use?
Agent Protocol is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Agent Protocol use?
About 1.6k tokens (SKILL.md is roughly 6.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.5k tokens, read only when the agent opens those files.
What are the alternatives to Agent Protocol?
Skills that share tags, products or a category with Agent Protocol: Agent Tool Builder (omer-metin/skills-for-antigravity, 162 stars), Tool Design (agentailor/fullstack-langgraph-nextjs-agent, 132 stars), Local AI Agents (microsoft/ai-agents-for-beginners, 77k stars) and Local AI Agents (microsoft/ai-agents-for-beginners, 77k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Agent Protocol?
borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 881 GitHub stars. The repository holds 349 skills in this directory. The repository was last updated on October 7, 2026.
Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.