Recording Analyzer
Extract keywords and patterns from converted text recordings.
Installation
- Make sure Claude is on your device and in your terminal.
Skills load from
~/.claude/skills/when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then runclaudein any terminal to verify.One-time setupnpm i -g @anthropic-ai/claude-codeAlready have it? Skip ahead.
- Paste into Claude Code or into your terminal.
This copies the whole skill folder into
~/.claude/skills/analyze-terrylica/— the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.Faster alternative (instruction-only skills)
Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.
Quick install (SKILL.md only)Sign up to copy - Restart Claude Code.
Quit and reopen Claude Code (or any other agent that loads from
~/.claude/skills/). New skills are picked up on startup. - Just ask Claude.
Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.
Prefer to read the source first? Open on GitHub.
When Claude uses it
Semantic analysis of converted recordings. TRIGGERS - analyze cast, keyword extraction, find patterns.
What this skill does
/asciinema-tools:analyze
Run semantic analysis on converted .txt recordings.
Self-Evolving Skill: This skill improves through use. If instructions are wrong, parameters drifted, or a workaround was needed — fix this file immediately, don't defer. Only update for real, reproducible issues.
Arguments
| Argument | Description |
|---|---|
file | Path to .txt file |
-d, --domains | Domains: trading,ml,dev,claude |
-t, --type | Type: curated, auto, full, density |
--json | Output in JSON format |
--md | Save as markdown report |
--density | Include density analysis |
--jump | Jump to peak section after analysis |
Execution
Invoke the asciinema-analyzer skill with user-selected options.
Skip Logic
- If
fileprovided -> skip Phase 1 (file selection) - If
-tprovided -> skip Phase 2 (analysis type) - If
-dprovided -> skip Phase 3 (domain selection) - If
--json/--mdprovided -> skip Phase 6 (report format) - If
--jumpprovided -> auto-execute jump after analysis
Workflow
- Preflight: Check for .txt file
- Discovery: Find .txt files
- Selection: AskUserQuestion for file
- Type: AskUserQuestion for analysis type
- Domain: AskUserQuestion for domains (multi-select)
- Curated: Run ripgrep searches
- Auto: Run YAKE if selected
- Density: Calculate density windows if selected
- Format: AskUserQuestion for report format
- Next: AskUserQuestion for follow-up action
Examples
# Quick curated analysis for trading domain
/asciinema-tools:analyze session.txt -d trading -t curated
# Full analysis with density and JSON output
/asciinema-tools:analyze session.txt -t full --density --json
# Auto keyword discovery with markdown report
/asciinema-tools:analyze session.txt -t auto --md
Troubleshooting
| Issue | Cause | Solution |
|---|---|---|
| ripgrep not found | Not installed | brew install ripgrep |
| YAKE not available | Python package missing | uv pip install yake |
| No keywords found | Wrong domain or sparse content | Try -t auto for discovery |
Post-Execution Reflection
After this skill completes, check before closing:
- Did the command succeed? — If not, fix the instruction or error table that caused the failure.
- Did parameters or output change? — If the underlying tool's interface drifted, update Usage examples and Parameters table to match.
- Was a workaround needed? — If you had to improvise (different flags, extra steps), update this SKILL.md so the next invocation doesn't need the same workaround.
Only update if the issue is real and reproducible — not speculative.
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