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Transcript Processing

Folder: .github/skills/tsh-transcript-processing/
Used by: Business Analyst

Cleans raw workshop or meeting transcripts from small talk, filler words, and off-topic tangents. Extracts and structures business-relevant content into a standardized format.

Process​

Step 1: Identify Transcript Format​

Determine the input format:

  • Speaker-labelled transcript (e.g., [Speaker Name]: text)
  • Plain text notes without speaker labels
  • Timestamped transcript (e.g., [00:12:34] text)
  • Mixed format

Extract meeting metadata: date, duration, topic, and context.

Step 2: Identify Participants​

Scan for participant names and infer roles where obvious from context (e.g., "Product Owner", "Developer"). Do not guess roles when unclear.

Step 3: Remove Non-Business Content​

Systematically remove:

  • Greetings and sign-offs
  • Small talk and personal anecdotes
  • Filler words and verbal tics
  • Technical difficulties discussion
  • Off-topic tangents
  • Repetitive restatements (keep the clearest version)
tip

When in doubt about whether content is business-relevant, keep it. It is better to preserve potentially useful context than to accidentally remove important information.

Step 4: Group by Discussion Topics​

Organize cleaned content into logical topics with descriptive headings and bullet points. Maintain chronological order and consolidate disconnected parts of the same topic.

Step 5: Extract Key Decisions​

Identify explicit decisions ("We agreed to...") and implicit decisions (discussion converging on a direction). Note what was decided, who endorsed it, and any conditions.

Step 6: Extract Action Items and Open Questions​

Scan for commitments, assigned tasks, unanswered questions, and deferred items. Note the what, who, and any deadlines.

Step 7: Preserve Critical Raw Context​

Keep exact quotes where the original wording matters: requirements in business language, constraints from stakeholders, conflicting viewpoints, and domain-specific terminology.

Step 8: Save Output​

Generate the cleaned transcript following the cleaned-transcript.example.md template. Save to specifications/<workshop-name>/cleaned-transcript.md.

Connected Skills​

  • tsh-task-extracting — Uses the cleaned transcript as primary input for identifying epics and stories.