Agent skill
generate-agent-card
Generate an A2A agent card JSON by analyzing agent source code in a folder or GitHub URL. Studies the code to detect agent name, skills, tools, auth, protocol, and generates a spec-compliant agent card.
Install this agent skill to your Project
npx add-skill https://github.com/agentic-community/mcp-gateway-registry/tree/main/.claude/skills/generate-agent-card
SKILL.md
Generate A2A Agent Card
Generate an A2A (Agent-to-Agent) protocol agent card JSON file by analyzing the source code at $ARGUMENTS.
Steps
1. Carefully study the source code
Do NOT just skim the top-level files. Agents can be complex, multi-file projects. You MUST thoroughly explore the entire folder structure before generating the card.
If $ARGUMENTS is a local folder path, use Glob to find ALL Python files, YAML/JSON configs, and README files in the folder and its subfolders. Read every relevant file.
If $ARGUMENTS is a GitHub URL, use WebFetch to read the raw file contents. Follow imports to discover additional files.
Where to look (agents are not always a single file):
- Entrypoints:
main.py,app.py,agent_entrypoint.py,server.py,__main__.py - Tool definitions: tools may be in separate files like
tools/,skills/,functions/, or registered via decorators (@tool,@function_tool,@mcp_tool) - Multi-agent setups: look for orchestrator/supervisor patterns, multiple agent classes, agent registries, sub-agent folders
- Prompts and system messages: may be in separate files like
prompts/,templates/,system_prompt.txt, or as string constants - MCP server connections: look for MCP client configs,
mcp_servers,MCPClient, tool imports from MCP servers - these are skills the agent can use - Config files:
pyproject.toml,requirements.txt,.bedrock_agentcore.yaml,agent_config.yaml,docker-compose.yml - Sub-folders: check ALL subdirectories for additional agents, tools, or shared utilities
From the code, detect:
- Agent name: from constants, CLI args, config files, class names
- Description: from docstrings, README, module-level comments
- Skills/tools: from
@tooldecorators, tool lists, function definitions passed to agent frameworks (Strands, LangChain, CrewAI, AutoGen, etc.), MCP tool connections, imported tool modules - Multi-agent skills: if there are multiple agents (orchestrator, sub-agents), each agent's capabilities should be represented as skills
- MCP-sourced tools: if the agent connects to MCP servers, list those tools as skills too (read the MCP server configs to find tool names and descriptions)
- Input/output modes: text, images, files, structured data - check what the agent accepts and returns
- Protocol: HTTP (
HTTP+JSON), A2A (JSONRPC), MCP - Auth mechanism: IAM/SigV4, Cognito/JWT, API key, OAuth2
- Streaming support: from framework config, capabilities flags
- Version: from constants, pyproject.toml, or default to
1.0.0 - Endpoint URL: from
.bedrock_agentcore.yamlor deployment config if available
2. Generate the agent card JSON
Create a JSON file following the official A2A Agent Card specification (https://a2a-protocol.org/latest/specification/).
All mandatory fields MUST be present. Use camelCase for JSON field names.
Required fields
{
"name": "string - Human-readable agent name",
"description": "string - What the agent does",
"version": "string - e.g. 1.0.0",
"supportedInterfaces": [
{
"url": "string - Agent endpoint URL",
"protocolBinding": "string - JSONRPC or HTTP+JSON or GRPC",
"protocolVersion": "string - e.g. 1.0"
}
],
"capabilities": {
"streaming": false,
"pushNotifications": false
},
"defaultInputModes": ["text/plain"],
"defaultOutputModes": ["text/plain"],
"skills": [
{
"id": "string - unique skill id",
"name": "string - human-readable name",
"description": "string - what the skill does",
"tags": ["string"],
"examples": ["string - example prompts"]
}
]
}
Optional fields to include when detected
provider: Include if organization info is available. Requiresorganization(string) andurl(string).documentationUrl: Link to docs if found in README or code.iconUrl: Agent icon if found.securitySchemes: Include when auth is detected:- Cognito/JWT:
{"bearerAuth": {"httpAuthSecurityScheme": {"scheme": "Bearer", "description": "Cognito JWT bearer token"}}} - API Key:
{"apiKey": {"apiKeySecurityScheme": {"name": "x-api-key", "location": "header"}}} - IAM/SigV4:
{"sigv4": {"httpAuthSecurityScheme": {"scheme": "AWS4-HMAC-SHA256", "description": "AWS SigV4 request signing"}}}
- Cognito/JWT:
securityRequirements: Reference the schemes defined above, e.g.[{"schemes": {"bearerAuth": []}}]
3. Populate skills correctly
- Find ALL tools/functions the agent exposes
- For each tool, create a skill entry with:
id: snake_case identifiername: Human-readable namedescription: From the function docstring or tool descriptiontags: Relevant categories (e.g.["math", "calculator"],["search", "web"])examples: 2-3 example prompts showing usage
4. Set the endpoint URL
- Check for
.bedrock_agentcore.yamlin the agent folder and read the ARN/endpoint if available - If no config found, use placeholder:
https://<AGENT_ENDPOINT_URL>/
5. Detect protocol binding
- A2A agents (a2a_server, A2AServer, port 9000, protocol="A2A"): use
JSONRPC - HTTP agents (BedrockAgentCoreApp, REST endpoints): use
HTTP+JSON - Default to
JSONRPC
6. Save the output
- Name the file
{agent_name}_agent_card.jsonusing the detected agent name in snake_case - Save it in the agent's folder (same folder as the source code)
- Pretty-print with 2-space indentation
7. Validate the generated JSON
After writing the file, validate it by running this Python script via Bash:
python3 -c "
import json
import sys
file_path = '<OUTPUT_FILE_PATH>'
# Step 1: JSON format check
try:
with open(file_path) as f:
card = json.load(f)
print('PASS: Valid JSON format')
except json.JSONDecodeError as e:
print(f'FAIL: Invalid JSON - {e}')
sys.exit(1)
# Step 2: Required top-level fields
errors = []
TOP_LEVEL_REQUIRED = ['name', 'description', 'version', 'supportedInterfaces', 'capabilities', 'defaultInputModes', 'defaultOutputModes', 'skills']
for field in TOP_LEVEL_REQUIRED:
if field not in card:
errors.append(f'Missing required top-level field: {field}')
elif field in ('name', 'description', 'version') and not isinstance(card[field], str):
errors.append(f'{field} must be a string')
elif field in ('defaultInputModes', 'defaultOutputModes', 'skills', 'supportedInterfaces') and not isinstance(card[field], list):
errors.append(f'{field} must be an array')
elif field == 'capabilities' and not isinstance(card[field], dict):
errors.append(f'{field} must be an object')
# Step 3: Validate supportedInterfaces entries
INTERFACE_REQUIRED = ['url', 'protocolBinding', 'protocolVersion']
for i, iface in enumerate(card.get('supportedInterfaces', [])):
for field in INTERFACE_REQUIRED:
if field not in iface:
errors.append(f'supportedInterfaces[{i}] missing required field: {field}')
binding = iface.get('protocolBinding', '')
if binding and binding not in ('JSONRPC', 'GRPC', 'HTTP+JSON'):
errors.append(f'supportedInterfaces[{i}].protocolBinding must be JSONRPC, GRPC, or HTTP+JSON, got: {binding}')
if not card.get('supportedInterfaces'):
errors.append('supportedInterfaces must have at least one entry')
# Step 4: Validate skills entries
SKILL_REQUIRED = ['id', 'name', 'description', 'tags']
for i, skill in enumerate(card.get('skills', [])):
for field in SKILL_REQUIRED:
if field not in skill:
errors.append(f'skills[{i}] missing required field: {field}')
if 'tags' in skill and not isinstance(skill['tags'], list):
errors.append(f'skills[{i}].tags must be an array')
# Step 5: Validate defaultInputModes/defaultOutputModes are non-empty
if not card.get('defaultInputModes'):
errors.append('defaultInputModes must have at least one entry')
if not card.get('defaultOutputModes'):
errors.append('defaultOutputModes must have at least one entry')
# Step 6: Validate provider if present
if 'provider' in card and card['provider'] is not None:
for field in ('organization', 'url'):
if field not in card['provider']:
errors.append(f'provider missing required field: {field}')
# Step 7: Report results
if errors:
print(f'FAIL: {len(errors)} validation error(s):')
for e in errors:
print(f' - {e}')
sys.exit(1)
else:
skill_count = len(card.get('skills', []))
iface_count = len(card.get('supportedInterfaces', []))
print(f'PASS: All mandatory fields present ({iface_count} interface(s), {skill_count} skill(s))')
"
Replace <OUTPUT_FILE_PATH> with the actual path of the generated JSON file.
If validation fails, fix the errors in the JSON and re-run validation until all checks pass. Do NOT report success to the user until validation passes.
8. Report results
After validation passes, output results in EXACTLY this format:
Validation passed. Here's a summary of the generated agent card:
Output file: <filename>.json
Detected from code:
- Agent name: <AgentName> (from <how it was detected, e.g. Strands agent with BedrockAgentCoreApp>)
- Skills: <count> - <skill_id> (<brief description>), <skill_id> (<brief description>), ...
- Protocol: <HTTP+JSON or JSONRPC> (<why, e.g. uses BedrockAgentCoreApp on port 8080>)
- Auth: <auth mechanisms detected, e.g. IAM/SigV4 (default) + Cognito JWT (optional)>
- Streaming: <true or false>
- Endpoint URL: <source, e.g. From .bedrock_agentcore.yaml - uses the my_agent deployment ARN (account ..., region ...)> or <Placeholder used - no deployment config found>
If validation fails, show the errors first, fix them, re-validate, and only show the summary above after all checks pass.
Reference template
Use this as a structural reference (from simple-a2a-agent):
{
"name": "SimpleCalculatorAgent",
"description": "A simple calculator agent that can evaluate mathematical expressions.",
"version": "1.0.0",
"supportedInterfaces": [
{
"url": "https://bedrock-agentcore.us-east-1.amazonaws.com/runtimes/<encoded-arn>/invocations/",
"protocolBinding": "JSONRPC",
"protocolVersion": "1.0"
}
],
"capabilities": {
"streaming": true,
"pushNotifications": false
},
"defaultInputModes": ["text/plain"],
"defaultOutputModes": ["text/plain"],
"skills": [
{
"id": "calculator",
"name": "Calculator",
"description": "Evaluate a mathematical expression and return the result.",
"tags": ["math", "calculator", "arithmetic"],
"examples": [
"What is 42 * 17?",
"Calculate the square root of 144",
"What is 15% of 200?"
]
}
]
}
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