interview-transcription

interview-transcription is a skill for Claude Code, Codex from jamditis/claude-skills-journalism. It costs 26 tokens per session (3,364 once invoked), scanned A, original, MIT.

A workflow for managing interview recordings and turning audio or video into transcripts and timestamped quotes. It covers practical recording settings and preparation of material for publication.

In plain words
What is it for?
Use it to process recordings, create transcripts, organise notes, extract timestamped quotes, and convert spoken material into publishable quotes.
Why use it?
It helps journalists keep recordings organised and find exact sections for fact-checking or attribution.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the journalism-core plugin — 16 skills shipped together

Good fit Use it to process recordings, create transcripts, organise notes, extract timestamped quotes, and convert spoken material into publishable quotes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jamditis/claude-skills-journalism/interview-transcription
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add jamditis/claude-skills-journalism --skill interview-transcription
Clone the repo
git clone --depth 1 https://github.com/jamditis/claude-skills-journalism

Made for: Claude Code, Codex.

Or install journalism-core, the plugin that ships this one along with the rest of its 16 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for interview-transcription

README.md
[![agentmods](https://agentmods.dev/badge/skills/jamditis/claude-skills-journalism/interview-transcription/github.svg)](https://agentmods.dev/skills/jamditis/claude-skills-journalism/interview-transcription)
Your own site
<a href="https://agentmods.dev/skills/jamditis/claude-skills-journalism/interview-transcription"><img src="https://agentmods.dev/badge/skills/jamditis/claude-skills-journalism/interview-transcription/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for interview-transcription

Your own site · 80×15
<a href="https://agentmods.dev/skills/jamditis/claude-skills-journalism/interview-transcription"><img src="https://agentmods.dev/badge/skills/jamditis/claude-skills-journalism/interview-transcription.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,364 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00026 $0.03364
Opus 5.5 $0.00010 $0.01346
Sonnet 5.5 $0.00005 $0.00673
Haiku 4.5 $0.00003 $0.00336

Measured 2d ago against content hash 875638039a3a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

interview-transcription scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

subprocess.run(cmd, check=True, capture_output=True)
journalism-core/skills/interview-transcription/SKILL.md · 423 lines

How it starts

The opening of the file, as written. The whole thing — 423 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Interview transcription and management

Practical workflows for journalists managing interviews from preparation through publication.

When to activate

  • Preparing questions for an interview
  • Processing audio/video recordings
  • Creating or managing transcripts
  • Organizing notes from multiple sources
  • Building a source relationship database
  • Generating timestamped quotes for fact-checking
  • Converting recordings to publishable quotes

Recording setup for transcription

For pre-interview research, question design, attribution agreements, and consent scripts, use the interview-prep skill. The notes here cover only the recording configuration that affects transcription quality.

# Standard recording configuration for clean transcription
RECORDING_SETTINGS = {
    'format': 'wav',           # Lossless for transcription
    'sample_rate': 16000,      # Whisper resamples to 16k anyway; 16k saves disk
    'channels': 1,             # Mono is fine for speech; stereo only if mics are positionally distinct
    'backup': True,            # Always run a backup recorder
}

# File naming convention
# YYYY-MM-DD_source-lastname_topic.wav
# Example: 2026-05-08_smith_budget-hearing.wav

Two-device rule. Always record on two devices. Phone as backup minimum. If using a wireless lav mic, the recorder built into the lav unit is one device; the phone running a backup app is the second.

Mono is preferred unless each speaker has their own dedicated microphone routed to a distinct channel. Stereo with both speakers bleeding into both channels is worse for diarization than clean mono.

Transcription workflows

Automated transcription pipeline

Vanilla OpenAI Whisper transcribes audio to text but does not assign speaker labels. To get diarized output ("Speaker 1:" / "Speaker 2:" / etc.) you need a tool that combines Whisper with a diarization model, typically WhisperX (m-bain/whisperX), which wraps faster-whisper transcription with pyannote.audio diarization and produces word-level timestamps with speaker IDs in one pass.

Read the full file on GitHub · 423 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago Changed · +1 lines 875638039a3a
  2. 1mo ago First seen · 422 lines · 26 tokens per session scan A 1b73a54a40c7

Subscribe to this mod's changes

interview-transcription is a skill published in the GitHub repository jamditis/claude-skills-journalism (434 stars, last pushed 2d ago), licensed MIT. It adds 26 tokens to every session and 3,364 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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