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analyze

Semantic analysis of converted recordings. TRIGGERS - analyze cast, keyword extraction, find patterns.

terrylica/cc-skills0installs75stars

SKILL.md

Full skill instructions

/​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

ArgumentDescription
filePath to .txt file
-d, --domainsDomains: trading,ml,dev,claude
-t, --typeType: curated, auto, full, density
--jsonOutput in JSON format
--mdSave as markdown report
--densityInclude density analysis
--jumpJump to peak section after analysis

Execution

Invoke the asciinema-analyzer skill with user-selected options.

Skip Logic

  • If file provided -> skip Phase 1 (file selection)
  • If -t provided -> skip Phase 2 (analysis type)
  • If -d provided -> skip Phase 3 (domain selection)
  • If --json/​--md provided -> skip Phase 6 (report format)
  • If --jump provided -> auto-execute jump after analysis

Workflow

  1. Preflight: Check for .txt file
  2. Discovery: Find .txt files
  3. Selection: AskUserQuestion for file
  4. Type: AskUserQuestion for analysis type
  5. Domain: AskUserQuestion for domains (multi-select)
  6. Curated: Run ripgrep searches
  7. Auto: Run YAKE if selected
  8. Density: Calculate density windows if selected
  9. Format: AskUserQuestion for report format
  10. 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

IssueCauseSolution
ripgrep not foundNot installedbrew install ripgrep
YAKE not availablePython package missinguv pip install yake
No keywords foundWrong domain or sparse contentTry -t auto for discovery

Post-Execution Reflection

After this skill completes, check before closing:

  1. Did the command succeed? — If not, fix the instruction or error table that caused the failure.
  2. Did parameters or output change? — If the underlying tool's interface drifted, update Usage examples and Parameters table to match.
  3. 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.