rest-api-tool
Skill0 starsChanged 6 months agoMITView on GitHub
Invoke external REST APIs from inside an agent using httpx.AsyncClient. Supports GET/POST/PUT/DELETE with optional auth header propagation from the execution context. Use when an agent needs to call external services, microservices, or webhooks.
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The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 0 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 81
Use unittest.mock.patch to intercept httpx.AsyncClient within the tool call's context.
- Very specific: line 162
Always override the tool name with @tool(name="rest_api_tool") since the auto-generated name for RestAPITool would be rest_a_p_i_tool.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Use
codemap find "RestAPITool"after adding the pattern to your project.
REST API Invocation Tool with Auth Propagation
An httpx-based @tool() class that supports all common HTTP methods and
propagates authorization headers from the calling request context.
Critical rule — name override for acronym classes
RestAPITool would auto-generate rest_a_p_i_tool. Override explicitly:
@tool(name="rest_api_tool")
class RestAPITool:
...Pattern
from lauren_ai._tools import tool, ToolContext
import httpx
import json
@tool(name="rest_api_tool")
class RestAPITool:
"""Invoke a REST API endpoint.
Args:
url: The full URL to call (or path when base_url is set).
method: HTTP method (GET, POST, PUT, DELETE).
body: Optional JSON body for POST/PUT as a JSON string.
headers: Optional additional headers as a JSON string.
"""
def __init__(self, base_url: str = "", auth_header: str | None = None):
self._base_url = base_url
self._auth_header = auth_header
async def run(
self,
ctx: ToolContext,
url: str,
method: str = "GET",
body: str = "",
headers: str = "",
) -> dict:
full_url = self._base_url + url if url.startswith("/") else url
extra_headers = json.loads(headers) if headers else {}
# Static auth header from tool configuration
if self._auth_header:
extra_headers["Authorization"] = self._auth_header
# Dynamic auth propagation from the originating request
if ctx.execution_context and ctx.execution_context.request:
auth = ctx.execution_context.request.headers.get("authorization")
if auth:
extra_headers["Authorization"] = auth
async with httpx.AsyncClient(timeout=30.0) as client:
try:
method_fn = getattr(client, method.lower())
response = await method_fn(
full_url,
json=json.loads(body) if body else None,
headers=extra_headers,
)
return {"status": response.status_code, "body": response.text[:2000]}
except Exception as e:
return {"error": str(e)}AgentRunner test pattern
Use unittest.mock.patch to intercept httpx.AsyncClient within the tool
call's context. Pass the tool instance to @use_tools and use _Capture to
inspect results.
import json
from unittest.mock import AsyncMock, MagicMock, patch
from lauren_ai._agents import AgentContext, agent, use_tools
from lauren_ai._tools import ToolResult
from lauren_ai._transport import Completion, TokenUsage
from lauren_ai.testing import TestClient
class _Capture:
def __init__(self):
self.captured: list[ToolResult] = []
async def on_tool_result(self, result: ToolResult, ctx: AgentContext) -> ToolResult | None:
self.captured.append(result)
return None
def _c(text):
return Completion(id="c1", model="mock", content=text, tool_calls=[],
stop_reason="end_turn", usage=TokenUsage(10, 5))
def _make_agent(tool_instance):
@agent(model=None, system="REST API test agent")
@use_tools(tool_instance)
class RestAPITestAgent(_Capture):
def __init__(self):
_Capture.__init__(self)
return RestAPITestAgent()
def test_get_request_is_made():
tool_inst = RestAPITool()
agent_inst = _make_agent(tool_inst)
client = TestClient(agent_inst)
mock_resp = MagicMock(status_code=200, text='{"ok": true}')
mock_client = MagicMock()
mock_client.__aenter__ = AsyncMock(return_value=mock_client)
mock_client.__aexit__ = AsyncMock(return_value=None)
mock_client.get = AsyncMock(return_value=mock_resp)
with patch("httpx.AsyncClient", return_value=mock_client):
client.mock.queue_tool_use(
"rest_api_tool",
{"url": "https://api.example.com/data", "method": "GET"},
)
client.mock.queue_response(_c("Data retrieved."))
client.run("Fetch data")
data = json.loads(agent_inst.captured[0].content)
assert data["status"] == 200Auth propagation chain
HTTP request ─► Lauren controller
│ execution_context.request.headers["authorization"]
▼
AgentRunner.run(..., execution_context=ctx)
│
▼
ToolContext.execution_context
│
▼
RestAPITool.run → httpx call with Authorization headerNotes
httpx.AsyncClientis created per-call. For high-throughput use, inject a shared client via the constructor (DI-friendly).bodyandheadersare JSON strings so they can be passed through the LLM tool-call JSON encoding.- Cap
response.text[:2000]to avoid flooding the model context. - Always override the tool name with
@tool(name="rest_api_tool")since the auto-generated name forRestAPIToolwould berest_a_p_i_tool.
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