用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/Lord1Egypt/ai-skillforge --skill data-claude-api-reference-curl命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
Implementing WCAG accessibility guidelines, semantic HTML5, and screen reader ARIA roles.
How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
基于 SOC 职业分类
正在显示 SKILL.md
| name | Data: Claude API reference — cURL |
| description | Raw API reference for Claude API for use with cURL or else Raw HTTP |
| ccVersion | 2.1.154 |
| allowed-tools | Read Write Edit Bash |
| license | BSD-3-Clause license |
| metadata | {"skill-author":"Lord1Egypt"} |
Use these examples when the user needs raw HTTP requests or is working in a language without an official SDK.
export ANTHROPIC_API_KEY="your-api-key"
curl https://api.anthropic.com/v1/messages \
-H "Content-Type: application/json" \
-H "x-api-key: $ANTHROPIC_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-d '{
"model": "{{OPUS_ID}}",
"max_tokens": 16000,
"messages": [
{"role": "user", "content": "What is the capital of France?"}
]
}'
Use jq to extract fields from the JSON response. Do not use grep/sed —
JSON strings can contain any character and regex parsing will break on quotes,
escapes, or multi-line content.
# Capture the response, then extract fields
response=$(curl -s https://api.anthropic.com/v1/messages \
-H "Content-Type: application/json" \
-H "x-api-key: $ANTHROPIC_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-d '{"model":"{{OPUS_ID}}","max_tokens":16000,"messages":[{"role":"user","content":"Hello"}]}')
# Print the first text block (-r strips the JSON quotes)
echo "$response" | jq -r '.content[0].text'
# Read usage fields
input_tokens=$(echo "$response" | jq -r '.usage.input_tokens')
output_tokens=$(echo "$response" | jq -r '.usage.output_tokens')
# Read stop reason (for tool-use loops)
stop_reason=$(echo "$response" | jq -r '.stop_reason')
# Extract all text blocks (content is an array; filter to type=="text")
echo "$response" | jq -r '.content[] | select(.type == "text") | .text'
curl https://api.anthropic.com/v1/messages \
-H "Content-Type: application/json" \
-H "x-api-key: $ANTHROPIC_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-d '{
"model": "{{OPUS_ID}}",
"max_tokens": 64000,
"stream": true,
"messages": [{"role": "user", "content": "Write a haiku"}]
}'
The response is a stream of Server-Sent Events:
event: message_start
data: {"type":"message_start","message":{"id":"msg_...","type":"message",...}}
event: content_block_start
data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}
event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"Hello"}}
event: content_block_stop
data: {"type":"content_block_stop","index":0}
event: message_delta
data: {"type":"message_delta","delta":{"stop_reason":"end_turn"},"usage":{"output_tokens":12}}
event: message_stop
data: {"type":"message_stop"}
curl https://api.anthropic.com/v1/messages \
-H "Content-Type: application/json" \
-H "x-api-key: $ANTHROPIC_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-d '{
"model": "{{OPUS_ID}}",
"max_tokens": 16000,
"tools": [{
"name": "get_weather",
"description": "Get current weather for a location",
"input_schema": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "City name"}
},
"required": ["location"]
}
}],
"messages": [{"role": "user", "content": "What is the weather in Paris?"}]
}'
When Claude responds with a tool_use block, send the result back:
curl https://api.anthropic.com/v1/messages \
-H "Content-Type: application/json" \
-H "x-api-key: $ANTHROPIC_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-d '{
"model": "{{OPUS_ID}}",
"max_tokens": 16000,
"tools": [{
"name": "get_weather",
"description": "Get current weather for a location",
"input_schema": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "City name"}
},
"required": ["location"]
}
}],
"messages": [
{"role": "user", "content": "What is the weather in Paris?"},
{"role": "assistant", "content": [
{"type": "text", "text": "Let me check the weather."},
{"type": "tool_use", "id": "toolu_abc123", "name": "get_weather", "input": {"location": "Paris"}}
]},
{"role": "user", "content": [
{"type": "tool_result", "tool_use_id": "toolu_abc123", "content": "72°F and sunny"}
]}
]
}'
Put cache_control on the last block of the stable prefix. See shared/prompt-caching.md for placement patterns and the silent-invalidator audit checklist.
curl https://api.anthropic.com/v1/messages \
-H "Content-Type: application/json" \
-H "x-api-key: $ANTHROPIC_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-d '{
"model": "{{OPUS_ID}}",
"max_tokens": 16000,
"system": [
{"type": "text", "text": "<large shared prompt...>", "cache_control": {"type": "ephemeral"}}
],
"messages": [{"role": "user", "content": "Summarize the key points"}]
}'
For 1-hour TTL: "cache_control": {"type": "ephemeral", "ttl": "1h"}. Top-level "cache_control" on the request body auto-places on the last cacheable block. Verify hits via the response usage.cache_creation_input_tokens / usage.cache_read_input_tokens fields.
Opus 4.8, Opus 4.7, Opus 4.6, and Sonnet 4.6: Use adaptive thinking.
budget_tokensis removed on Opus 4.8 and 4.7 (400 if sent); deprecated on Opus 4.6 and Sonnet 4.6. Older models: Use"type": "enabled"with"budget_tokens": N(must be <max_tokens, min 1024).
# Opus 4.8 / 4.7 / 4.6: adaptive thinking (recommended)
curl https://api.anthropic.com/v1/messages \
-H "Content-Type: application/json" \
-H "x-api-key: $ANTHROPIC_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-d '{
"model": "{{OPUS_ID}}",
"max_tokens": 16000,
"thinking": {
"type": "adaptive"
},
"output_config": {
"effort": "high"
},
"messages": [{"role": "user", "content": "Solve this step by step..."}]
}'
| Header | Value | Description |
|---|---|---|
Content-Type | application/json | Required |
x-api-key | Your API key | Authentication |
anthropic-version | 2023-06-01 | API version |
anthropic-beta | Beta feature IDs | Required for beta features |