fabrico-transcript-processing

name	fabrico-transcript-processing
description	Clean transcripts and extract decisions, action items, and open questions.

Transcript Processing

This skill helps you clean raw workshop or meeting transcripts and produce a structured, business-relevant document. It removes noise (small talk, greetings, filler words, off-topic tangents) while preserving all actionable and business-critical discussion points.

Transcript Processing Process

Use the checklist below and track your progress:

Processing progress:
- [ ] Step 1: Identify transcript format and meeting metadata
- [ ] Step 2: Identify and tag participants
- [ ] Step 3: Remove non-business content
- [ ] Step 4: Group remaining content by discussion topics
- [ ] Step 5: Extract key decisions
- [ ] Step 6: Extract action items and open questions
- [ ] Step 7: Preserve critical raw context
- [ ] Step 8: Save the cleaned transcript

Step 1: Identify transcript format and meeting metadata

Determine the format of the raw transcript:

• Speaker-labelled transcript (e.g., [Speaker Name]: text)
• Plain text notes without speaker labels
• Timestamped transcript (e.g., [00:12:34] text)
• Mixed format
• PDF document (transcript or meeting notes exported/provided as PDF — use file-reading tools to extract text content first)

Extract meeting metadata where available:

• Date and time of the workshop
• Duration (if timestamps are present, calculate from first to last entry)
• Workshop topic or title
• Context (e.g., "Discovery workshop for Project X, Sprint 3 planning")

If metadata is not explicitly stated in the transcript, ask the user to provide it.

Step 2: Identify and tag participants

Scan the transcript for participant names or speaker labels. For each participant:

• Note their name or identifier
• Infer their role if mentioned or obvious from context (e.g., "Product Owner", "Developer", "Client stakeholder")
• If roles are not clear, list participants without roles — do not guess

Step 3: Remove non-business content

Systematically identify and remove:

• Greetings and sign-offs: "Hi everyone", "Let's wrap up", "Have a good weekend"
• Small talk: Weather, personal anecdotes, unrelated banter
• Filler words and verbal tics: "um", "uh", "you know", "like" (when used as filler)
• Technical difficulties discussion: "Can you hear me?", "Let me share my screen", "You're on mute"
• Off-topic tangents: Discussions clearly unrelated to the workshop's purpose
• Repetitive restatements: When the same point is made multiple times, keep the clearest version

Important: 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 remaining content by discussion topics

Analyze the cleaned content and organize it into logical discussion topics:

• Identify natural topic boundaries (when the conversation shifts to a new subject)
• Create descriptive topic headings that summarize the theme
• Under each topic, list the key points discussed as bullet points
• Attribute points to speakers when speaker labels are available
• Maintain chronological order within each topic
• If a topic spans multiple disconnected parts of the transcript, consolidate them under one heading

Step 5: Extract key decisions

Review the structured content and identify explicit and implicit decisions:

• Explicit decisions: Statements like "We agreed to...", "The decision is...", "Let's go with..."
• Implicit decisions: When discussion converges on a direction without formal declaration
• For each decision, note:
  • What was decided
  • Who made or endorsed the decision (if clear)
  • Any conditions or caveats attached

Step 6: Extract action items and open questions

Scan for action items:

• Commitments to do something (e.g., "I'll prepare the wireframes by Friday")
• Assigned tasks (e.g., "Can you check the API documentation?")
• For each action item, note: what, who (if assigned), and any deadline mentioned

Scan for open questions:

• Unanswered questions raised during the workshop
• Items deferred for later discussion ("We'll revisit this next week")
• Ambiguities that were acknowledged but not resolved

Step 7: Preserve critical raw context

Identify and preserve exact quotes or passages where the original wording is important:

• Requirements stated in specific business language
• Constraints or limitations mentioned by stakeholders
• Conflicting viewpoints that need to be captured verbatim
• Domain-specific terminology defined or explained during the workshop

Place these in a "Preserved Context" section with attribution to the speaker.

Step 8: Save the cleaned transcript

Generate the final output following the ./cleaned-transcript.example.md template.

Save the file to specifications/<workshop-name>/cleaned-transcript.md.

Review the output to ensure:

• No business-relevant content was accidentally removed
• Topics are logically grouped and clearly labelled
• Decisions, action items, and open questions are complete
• The document is readable and useful as a standalone reference

Connected Skills

• fabrico-task-extracting - uses the cleaned transcript as a primary input for identifying epics and stories