基于 SOC 职业分类
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/duclm1x1/Dive-Ai --skill raysurfer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。
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Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
| name | raysurfer |
| description | Cache and reuse code from prior AI agent executions via Raysurfer. Search before coding, upload after success. |
| argument-hint | [search query or "upload"] |
| allowed-tools | ["Bash","Read","Write","Edit","Grep","Glob"] |
You have access to Raysurfer, a code caching system that stores and retrieves code from prior AI agent executions. Always check the cache before writing new code and upload successful results afterward.
https://api.raysurfer.comRAYSURFER_API_KEY environment variableContent-Type: application/jsonFollow this sequence for every coding task:
Before writing any code, search for existing cached solutions.
To also include community public snippets (crawled from GitHub), add the X-Raysurfer-Public-Snips: true header.
curl -s -X POST https://api.raysurfer.com/api/retrieve/search \
-H "Authorization: Bearer $RAYSURFER_API_KEY" \
-H "Content-Type: application/json" \
-H "X-Raysurfer-Public-Snips: true" \
-d '{"task": "<describe the task here>", "top_k": 5, "min_verdict_score": 0.3}'
The response contains:
{
"matches": [
{
"code_block": {
"id": "uuid",
"name": "descriptive name",
"description": "what this code does",
"source": "the actual code content",
"language": "python"
},
"combined_score": 0.85,
"filename": "suggested_filename.py",
"thumbs_up": 12,
"thumbs_down": 1
}
],
"total_found": 3,
"cache_hit": true
}
Decision logic:
total_found > 0 and the top match has combined_score >= 0.7 and a favorable vote ratio (thumbs_up > thumbs_down), use the cached code.When a good cache hit is found:
source field from the best matching code_block.When no suitable cache hit exists:
After using cached code, report whether it worked:
curl -s -X POST https://api.raysurfer.com/api/store/cache-usage \
-H "Authorization: Bearer $RAYSURFER_API_KEY" \
-H "Content-Type: application/json" \
-d '{"code_block_id": "<id from the match>", "code_block_name": "<name from the match>", "code_block_description": "<description from the match>", "succeeded": true, "task": "<the task description>"}'
Set succeeded to true if the code ran correctly, false if it failed or needed significant changes.
After successfully generating and running new code (cache miss), upload it for future reuse:
curl -s -X POST https://api.raysurfer.com/api/store/execution-result \
-H "Authorization: Bearer $RAYSURFER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"task": "<describe what this code does>",
"file_written": {"path": "relative/path/to/file.py", "content": "<full file content>"},
"succeeded": true
}'
Only upload code that executed successfully. AI voting is enabled by default.
/raysurfer parse CSV and generate chart), run Step 1 with that query as the task.upload (e.g., /raysurfer upload), run Step 4 for the most recently generated code in the conversation.When $ARGUMENTS is provided, use it as: $ARGUMENTS
Ready-to-run scripts are in this skill's directory. Requires RAYSURFER_API_KEY to be set.
python search.py "Parse a CSV and plot a chart"
bun search.ts "Parse a CSV and plot a chart"
bash search.sh "Parse a CSV and plot a chart"
python upload.py "Generate a bar chart" chart.py
bun upload.ts "Generate a bar chart" chart.py
bash upload.sh "Generate a bar chart" chart.py
RAYSURFER_API_KEY is set before making API calls. If unset, inform the user and skip cache operations.task strings that capture what the code does, not how it does it (e.g., "Parse CSV file and generate a bar chart with matplotlib" rather than "run pandas read_csv and plt.bar").| Action | Endpoint | Method |
|---|---|---|
| Search cache | /api/retrieve/search | POST |
| Upload code | /api/store/execution-result | POST |
| Vote on code | /api/store/cache-usage | POST |
See references/api-reference.md for full request and response schemas.