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chore: update claude-api skill [auto-sync] (#729)

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2026-03-22 12:16:01 -04:00
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parent b0cbd3df15
commit 887114fd09
24 changed files with 1625 additions and 169 deletions
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skills/claude-api/python/claude-api/README.md
+21 -15
View File
@@ -28,12 +28,16 @@ async_client = anthropic.AsyncAnthropic()
```python
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[
{"role": "user", "content": "What is the capital of France?"}
]
)
print(response.content[0].text)
# response.content is a list of content block objects (TextBlock, ThinkingBlock,
# ToolUseBlock, ...). Check .type before accessing .text.
for block in response.content:
if block.type == "text":
print(block.text)
```
---
@@ -43,7 +47,7 @@ print(response.content[0].text)
```python
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
system="You are a helpful coding assistant. Always provide examples in Python.",
messages=[{"role": "user", "content": "How do I read a JSON file?"}]
)
@@ -63,7 +67,7 @@ with open("image.png", "rb") as f:
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[{
"role": "user",
"content": [
@@ -86,7 +90,7 @@ response = client.messages.create(
```python
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[{
"role": "user",
"content": [
@@ -116,7 +120,7 @@ Use top-level `cache_control` to automatically cache the last cacheable block in
```python
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
cache_control={"type": "ephemeral"}, # auto-caches the last cacheable block
system="You are an expert on this large document...",
messages=[{"role": "user", "content": "Summarize the key points"}]
@@ -130,7 +134,7 @@ For fine-grained control, add `cache_control` to specific content blocks:
```python
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
system=[{
"type": "text",
"text": "You are an expert on this large document...",
@@ -142,7 +146,7 @@ response = client.messages.create(
# With explicit TTL (time-to-live)
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
system=[{
"type": "text",
"text": "You are an expert on this large document...",
@@ -228,13 +232,15 @@ class ConversationManager:
response = self.client.messages.create(
model=self.model,
max_tokens=kwargs.get("max_tokens", 1024),
max_tokens=kwargs.get("max_tokens", 16000),
system=self.system,
messages=self.messages,
**kwargs
)
assistant_message = response.content[0].text
assistant_message = next(
(b.text for b in response.content if b.type == "text"), ""
)
self.messages.append({"role": "assistant", "content": assistant_message})
return assistant_message
@@ -259,7 +265,7 @@ response2 = conversation.send("What's my name?") # Claude remembers "Alice"
### Compaction (long conversations)
> **Beta, Opus 4.6 only.** When conversations approach the 200K context window, compaction automatically summarizes earlier context server-side. The API returns a `compaction` block; you must pass it back on subsequent requests — append `response.content`, not just the text.
> **Beta, Opus 4.6 and Sonnet 4.6.** When conversations approach the 200K context window, compaction automatically summarizes earlier context server-side. The API returns a `compaction` block; you must pass it back on subsequent requests — append `response.content`, not just the text.
```python
import anthropic
@@ -273,7 +279,7 @@ def chat(user_message: str) -> str:
response = client.beta.messages.create(
betas=["compact-2026-01-12"],
model="claude-opus-4-6",
max_tokens=4096,
max_tokens=16000,
messages=messages,
context_management={
"edits": [{"type": "compact_20260112"}]
@@ -316,7 +322,7 @@ The `stop_reason` field in the response indicates why the model stopped generati
# Automatic caching (simplest — caches the last cacheable block)
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
cache_control={"type": "ephemeral"},
system=large_document_text, # e.g., 50KB of context
messages=[{"role": "user", "content": "Summarize the key points"}]
@@ -332,14 +338,14 @@ response = client.messages.create(
# Default to Opus for most tasks
response = client.messages.create(
model="claude-opus-4-6", # $5.00/$25.00 per 1M tokens
max_tokens=1024,
max_tokens=16000,
messages=[{"role": "user", "content": "Explain quantum computing"}]
)
# Use Sonnet for high-volume production workloads
standard_response = client.messages.create(
model="claude-sonnet-4-6", # $3.00/$15.00 per 1M tokens
max_tokens=1024,
max_tokens=16000,
messages=[{"role": "user", "content": "Summarize this document"}]
)
skills/claude-api/python/claude-api/batches.md
+8 -5
View File
@@ -27,7 +27,7 @@ message_batch = client.messages.batches.create(
custom_id="request-1",
params=MessageCreateParamsNonStreaming(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[{"role": "user", "content": "Summarize climate change impacts"}]
)
),
@@ -35,7 +35,7 @@ message_batch = client.messages.batches.create(
custom_id="request-2",
params=MessageCreateParamsNonStreaming(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[{"role": "user", "content": "Explain quantum computing basics"}]
)
),
@@ -75,7 +75,9 @@ print(f"Errored: {batch.request_counts.errored}")
for result in client.messages.batches.results(message_batch.id):
match result.result.type:
case "succeeded":
print(f"[{result.custom_id}] {result.result.message.content[0].text[:100]}")
msg = result.result.message
text = next((b.text for b in msg.content if b.type == "text"), "")
print(f"[{result.custom_id}] {text[:100]}")
case "errored":
if result.result.error.type == "invalid_request":
print(f"[{result.custom_id}] Validation error - fix request and retry")
@@ -116,7 +118,7 @@ message_batch = client.messages.batches.create(
custom_id=f"analysis-{i}",
params=MessageCreateParamsNonStreaming(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
system=shared_system,
messages=[{"role": "user", "content": question}]
)
@@ -175,7 +177,8 @@ while True:
results = {}
for result in client.messages.batches.results(batch.id):
if result.result.type == "succeeded":
results[result.custom_id] = result.result.message.content[0].text
msg = result.result.message
results[result.custom_id] = next((b.text for b in msg.content if b.type == "text"), "")
for custom_id, classification in sorted(results.items()):
print(f"{custom_id}: {classification}")
skills/claude-api/python/claude-api/files-api.md
+8 -5
View File
@@ -37,7 +37,7 @@ print(f"Size: {uploaded.size_bytes} bytes")
```python
response = client.beta.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[{
"role": "user",
"content": [
@@ -52,7 +52,9 @@ response = client.beta.messages.create(
}],
betas=["files-api-2025-04-14"],
)
print(response.content[0].text)
for block in response.content:
if block.type == "text":
print(block.text)
```
### Image
@@ -64,7 +66,7 @@ image_file = client.beta.files.upload(
response = client.beta.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[{
"role": "user",
"content": [
@@ -141,7 +143,7 @@ questions = [
for question in questions:
response = client.beta.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[{
"role": "user",
"content": [
@@ -155,7 +157,8 @@ for question in questions:
betas=["files-api-2025-04-14"],
)
print(f"\nQ: {question}")
print(f"A: {response.content[0].text[:200]}")
text = next((b.text for b in response.content if b.type == "text"), "")
print(f"A: {text[:200]}")
# 3. Clean up when done
client.beta.files.delete(uploaded.id)
skills/claude-api/python/claude-api/streaming.md
+6 -6
View File
@@ -5,7 +5,7 @@
```python
with client.messages.stream(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=64000,
messages=[{"role": "user", "content": "Write a story"}]
) as stream:
for text in stream.text_stream:
@@ -17,7 +17,7 @@ with client.messages.stream(
```python
async with async_client.messages.stream(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=64000,
messages=[{"role": "user", "content": "Write a story"}]
) as stream:
async for text in stream.text_stream:
@@ -35,7 +35,7 @@ Claude may return text, thinking blocks, or tool use. Handle each appropriately:
```python
with client.messages.stream(
model="claude-opus-4-6",
max_tokens=16000,
max_tokens=64000,
thinking={"type": "adaptive"},
messages=[{"role": "user", "content": "Analyze this problem"}]
) as stream:
@@ -62,7 +62,7 @@ The Python tool runner currently returns complete messages. Use streaming for in
```python
with client.messages.stream(
model="claude-opus-4-6",
max_tokens=4096,
max_tokens=64000,
tools=tools,
messages=messages
) as stream:
@@ -80,7 +80,7 @@ with client.messages.stream(
```python
with client.messages.stream(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=64000,
messages=[{"role": "user", "content": "Hello"}]
) as stream:
for text in stream.text_stream:
@@ -127,7 +127,7 @@ def stream_with_progress(client, **kwargs):
try:
with client.messages.stream(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=64000,
messages=[{"role": "user", "content": "Write a story"}]
) as stream:
for text in stream.text_stream:
skills/claude-api/python/claude-api/tool-use.md
+24 -21
View File
@@ -28,7 +28,7 @@ def get_weather(location: str, unit: str = "celsius") -> str:
# The tool runner handles the agentic loop automatically
runner = client.beta.messages.tool_runner(
model="claude-opus-4-6",
max_tokens=4096,
max_tokens=16000,
tools=[get_weather],
messages=[{"role": "user", "content": "What's the weather in Paris?"}],
)
@@ -70,9 +70,10 @@ async with stdio_client(StdioServerParameters(command="mcp-server")) as (read, w
await mcp_client.initialize()
tools_result = await mcp_client.list_tools()
runner = await client.beta.messages.tool_runner(
# tool_runner is sync — returns the runner, not a coroutine
runner = client.beta.messages.tool_runner(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[{"role": "user", "content": "Use the available tools"}],
tools=[async_mcp_tool(t, mcp_client) for t in tools_result.tools],
)
@@ -90,7 +91,7 @@ from anthropic.lib.tools.mcp import mcp_message
prompt = await mcp_client.get_prompt(name="my-prompt")
response = await client.beta.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[mcp_message(m) for m in prompt.messages],
)
```
@@ -103,7 +104,7 @@ from anthropic.lib.tools.mcp import mcp_resource_to_content
resource = await mcp_client.read_resource(uri="file:///path/to/doc.txt")
response = await client.beta.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[{
"role": "user",
"content": [
@@ -142,7 +143,7 @@ messages = [{"role": "user", "content": user_input}]
while True:
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=4096,
max_tokens=16000,
tools=tools,
messages=messages
)
@@ -189,7 +190,7 @@ final_text = next(b.text for b in response.content if b.type == "text")
```python
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
tools=tools,
messages=[{"role": "user", "content": "What's the weather in Paris?"}]
)
@@ -204,7 +205,7 @@ for block in response.content:
followup = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
tools=tools,
messages=[
{"role": "user", "content": "What's the weather in Paris?"},
@@ -241,7 +242,7 @@ for block in response.content:
if tool_results:
followup = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
tools=tools,
messages=[
*previous_messages,
@@ -271,7 +272,7 @@ tool_result = {
```python
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
tools=tools,
tool_choice={"type": "tool", "name": "get_weather"}, # Force specific tool
messages=[{"role": "user", "content": "What's the weather in Paris?"}]
@@ -291,7 +292,7 @@ client = anthropic.Anthropic()
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=4096,
max_tokens=16000,
messages=[{
"role": "user",
"content": "Calculate the mean and standard deviation of [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]"
@@ -319,7 +320,7 @@ uploaded = client.beta.files.upload(file=open("sales_data.csv", "rb"))
# Code execution is GA; Files API is still beta (pass via extra_headers)
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=4096,
max_tokens=16000,
extra_headers={"anthropic-beta": "files-api-2025-04-14"},
messages=[{
"role": "user",
@@ -364,7 +365,7 @@ for block in response.content:
# First request: set up environment
response1 = client.messages.create(
model="claude-opus-4-6",
max_tokens=4096,
max_tokens=16000,
messages=[{"role": "user", "content": "Install tabulate and create data.json with sample data"}],
tools=[{"type": "code_execution_20260120", "name": "code_execution"}]
)
@@ -376,7 +377,7 @@ container_id = response1.container.id
response2 = client.messages.create(
container=container_id,
model="claude-opus-4-6",
max_tokens=4096,
max_tokens=16000,
messages=[{"role": "user", "content": "Read data.json and display as a formatted table"}],
tools=[{"type": "code_execution_20260120", "name": "code_execution"}]
)
@@ -416,7 +417,7 @@ client = anthropic.Anthropic()
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=2048,
max_tokens=16000,
messages=[{"role": "user", "content": "Remember that my preferred language is Python."}],
tools=[{"type": "memory_20250818", "name": "memory"}],
)
@@ -442,7 +443,7 @@ memory = MyMemoryTool()
# Use with tool runner
runner = client.beta.messages.tool_runner(
model="claude-opus-4-6",
max_tokens=2048,
max_tokens=16000,
tools=[memory],
messages=[{"role": "user", "content": "Remember my preferences"}],
)
@@ -477,7 +478,7 @@ client = anthropic.Anthropic()
response = client.messages.parse(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[{
"role": "user",
"content": "Extract: Jane Doe (jane@co.com) wants Enterprise, interested in API and SDKs, wants a demo."
@@ -496,7 +497,7 @@ print(contact.interests) # ["API", "SDKs"]
```python
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[{
"role": "user",
"content": "Extract info: John Smith (john@example.com) wants the Enterprise plan."
@@ -520,7 +521,9 @@ response = client.messages.create(
)
import json
data = json.loads(response.content[0].text)
# output_config.format guarantees the first block is text with valid JSON
text = next(b.text for b in response.content if b.type == "text")
data = json.loads(text)
```
### Strict Tool Use
@@ -528,7 +531,7 @@ data = json.loads(response.content[0].text)
```python
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[{"role": "user", "content": "Book a flight to Tokyo for 2 passengers on March 15"}],
tools=[{
"name": "book_flight",
@@ -553,7 +556,7 @@ response = client.messages.create(
```python
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=1024,
max_tokens=16000,
messages=[{"role": "user", "content": "Plan a trip to Paris next month"}],
output_config={
"format": {