Transcript Processor

Transcript Processor Skill

Modes

This skill has three modes. Infer from the user's request; ask only if genuinely ambiguous.

Default to clean unless the user explicitly asks for analysis or commentary.

Upgrade mode is a separate entry point — skip to the Upgrade section if the user provides an existing clean file.

Before doing anything: state the plan and wait for confirmation

Before running any script or writing any output, state the execution plan in this exact format and stop:

**Plan**
- Mode: clean / digest
- Output language: [e.g. English / Chinese / bilingual: EN transcript, ZH commentary]
- Translation: yes / no — [Q and A will / will not be translated to target language]
- Steps: 1. save transcript → 2. run parser → 3. clean Q/A → 4. if translation: translate Q/A → 5. if digest: add commentary per block → 6. if digest: add meta-analysis → 7. write file

Confirm to proceed.

For upgrade mode, use this plan format instead:

**Plan**
- Mode: upgrade (clean → digest)
- Input file: [filename]
- Commentary language: [e.g. Chinese]
- Steps: 1. read clean file → 2. add commentary per block → 3. add meta-analysis → 4. write digest file

Confirm to proceed.

Do not start executing until the user confirms. This catches mismatches in language, translation intent, and mode before any work is done.

Main flow (clean and digest modes)

Step 1: Run the parser

Before writing any Q/A blocks, always run the transcript parser script.

This is not optional. The script does mechanical timestamp-based segmentation that prevents omissions. Do not rely on reading and remembering — traverse, don't retrieve.

python3 scripts/parse_transcript.py <transcript_file>

The script outputs a numbered skeleton of all segments with timestamps and types (Q / A / QA-mixed). Review the skeleton, correct any misclassifications manually if needed, then proceed to cleaning.

If the transcript file is not yet saved to disk, write it first:

cat << 'TRANSCRIPT' > /tmp/transcript.txt
[paste transcript content]
TRANSCRIPT
python3 scripts/parse_transcript.py /tmp/transcript.txt

Step 2: Clean Q (questions)

Q is cleaned original speech. Remove only:

• Filler words: uh, um, you know, I mean, like, right (standalone)

Do NOT:

• Rephrase, reorder, or summarize
• Merge separate questions into one
• Remove the interviewer's framing, edge, or follow-up logic
• Drop the timestamp

Format:

**[timestamp]**

**Q:** Cleaned question text here.

Step 3: Clean A (answers)

A is cleaned original speech — not a summary, not a paraphrase. The speaker's own words must be preserved.

Remove only:

• Filler words: uh, um, you know, I mean, like, right (standalone)
• Repeated false starts: "I think I think I think" → "I think"
• Redundant hedges that repeat within the same sentence

Do NOT:

• Rephrase, reorder, or substitute words
• Compress or summarize
• Drop specific numbers, named products, or named people
• Editorialize (save that for Commentary in digest mode)

If the answer spans multiple transcript segments, combine them in order.

Step 4 (digest mode only): Write Commentary

Skip entirely in clean mode.

Commentary is independent analysis — not a restatement of A. For each exchange, ask:

1. Did they answer the question? If not, what did they pivot to, and why?
2. What structural tension did they avoid? (e.g. answering "is revenue up?" with "costs are down")
3. What's verifiable? Label claims: [verifiable] / [inference] / [industry consensus]
4. Does their analogy actually hold? Name it if it doesn't.

Depth: 1-2 sentences for minor topics, full paragraph for core topics.

Step 5 (digest mode only): Meta-analysis

Skip entirely in clean mode.

After all Q/A/Commentary blocks, add a final section identifying recurring patterns:

• Deflection patterns (e.g. "always cites historical data when asked about future risk")
• Framing choices (e.g. "consistently reframes competitor gaps as 'different markets'")
• The 2-3 moments of genuine candor (high-signal, stand out against the baseline)
• Claims that can be cross-checked against public records

Upgrade mode (separate entry point)

Use this path when the user provides an existing clean .md file and asks to add commentary or upgrade to digest. Do not run the parser. Do not touch Q or A text.

1. Read the existing clean file directly. Treat each Q/A block as a completed segment.
2. Add Commentary after each A block (same rules as Step 4 above).
3. Add Meta-analysis at the end (same rules as Step 5 above).
4. Write the result as a new file: [original_name]_digest.md

Output language, translation, and section labels

Translation rule

If the user specifies an output language different from the transcript language, translate Q and A into the target language after cleaning. Translation comes after cleaning — clean first in the original language, then translate.

• "中文 clean" → clean English transcript, then translate Q and A to Chinese
• "bilingual" → keep original language for Q and A, target language for Commentary only
• "English clean" on an English transcript → no translation needed

When in doubt, include Translation: yes/no explicitly in the plan step and confirm with the user.

Section labels

Match labels to output language. Do not hardcode any single language.

For bilingual output (e.g. EN transcript + ZH commentary):

• Q and A: original language label + original language text
• Commentary: target language label + target language text

Document header:

> Source: [name / date]
> Mode: clean / digest
> Output language: [e.g. English / Chinese / bilingual: EN transcript, ZH commentary]
> Translation: yes / no
> Note: Q and A = cleaned original speech (fillers and false starts removed only)

File output

• Filename: [interviewee]_[source]_[mode].md — e.g. sundar_allin_digest.md, sundar_allin_clean_zh.md
• One file per mode/language combination
• Run scripts/check_digest.py on the output before presenting to the user

Common failure modes