npx skills add smithery/terrylica --skill ckvd-research
terrylica/crypto-kline-vision-data · Archived
ckvd-research
Research CKVD codebase for implementation details, patterns, or architecture questions. TRIGGERS - how does FCP work, understand data flow, find code, explore codebase, architecture questions.
Installation
npx skills add terrylica/crypto-kline-vision-data --skill ckvd-research
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skill md
SKILL.md3,440 B -
docs
SUMMARY.md213 B
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- First seen on skills.sh
- First recorded snapshot · 12 installs
SKILL.md
CKVD Codebase Research
Research the crypto-kline-vision-data codebase to answer questions about: $ARGUMENTS
Research Focus
Key Areas to Investigate
- FCP Implementation (
src/ckvd/core/sync/cryptoklinevision_data.py)
- How failover decisions are made - Cache → Vision → REST priority
- Provider Implementations (
src/ckvd/core/providers/binance/)
- Vision API client - REST API client - Cache manager
- Utilities (
src/ckvd/utils/)
- Market constraints and validation - Timestamp handling - DataFrame utilities
- Streaming Implementation (
src/ckvd/core/streaming/)
- KlineStream class and stream lifecycle - KlineUpdate dataclass structure - StreamConfig configuration options - WebSocket client connection handling - Async message loop patterns
Research Instructions
- Use Glob to find relevant files
- Use Grep to search for specific patterns
- Read key files to understand implementation
- Summarize findings with specific file:line references
Expected Output
Provide:
- Summary: Brief answer to the research question
- Key Files: Files most relevant to the topic
- Code References: Specific file:line references
- Related Topics: Other areas worth investigating
TodoWrite Task Templates
Template A: Investigate FCP Flow
1. Read src/ckvd/core/sync/crypto_kline_vision_data.py get_data() method
2. Trace cache check logic (get_cache_lazyframes in ckvd_cache_utils)
3. Trace Vision fetch logic (_fetch_from_vision)
4. Trace REST fallback logic (_fetch_from_rest)
5. Document FCP decision points with file:line references
Template B: Trace Data Source
1. Identify the data source module (Vision, REST, Cache)
2. Read the provider client implementation
3. Trace data flow from API call to DataFrame return
4. Document error handling and retry logic
5. Summarize with file:line references
Template C: Map Exception Handling
1. Read rest_exceptions.py and vision_exceptions.py
2. Grep for exception catch/raise patterns in core/
3. Map which exceptions trigger FCP fallback
4. Identify any silent failures or bare excepts
5. Document exception flow with file:line references
Template D: Investigate Streaming Architecture
1. Read src/ckvd/core/streaming/kline_stream.py (KlineStream class)
2. Understand stream lifecycle: create → subscribe → iterate → close
3. Research KlineUpdate dataclass (fields: open_time, close, open, high, low, volume, symbol, interval, is_closed)
4. Trace async context manager patterns (__aenter__, __aexit__)
5. Study WebSocket client initialization and message handling
6. Document stream state management and error handling
7. Summarize async patterns with file:line references
Post-Change Checklist
After modifying this skill:
- Key areas to investigate still match actual file paths
- Research instructions reference available tools
- Append changes to [references/evolution-log.md](./references/evolution-log.md)
References
- @references/evolution-log.md - Skill change history