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conference-report

Use when the user attended one or more sessions of a conference (with audio recordings + slide photos) and needs help building (1) faithful per-session…

Skill by KerberosClaw

IndexedMIT★ 79
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Use when the user attended one or more sessions of a conference (with audio recordings + slide photos) and needs help building (1) faithful per-session reconstructions in markdown (slide visuals + speaker transcript with Whisper hallucination annotations), and (2) a downstream report deliverable whose scope and format are decided interactively with the user. Pipeline phase (raw → mlx_whisper Chinese SRT → per-slide multimodal reconstruction → official agenda cross-check via Playwright if available) is deterministic. Report phase is interactive — always quiz user on scope (single-session / single-day / multi-day synthesis), format (existing template / free-form fallback), recipient (formal / informal), and any business workstream mapping before drafting.

Use cases: documents, presentations, testing, data

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/conference-report

What's inside

Skill name
conference-report
Description
Use when the user attended one or more sessions of a conference (with audio recordings + slide photos) and needs help building (1) faithful per-session reconstructions in markdown (slide visuals + speaker transcript with Whisper hallucination annotations), and (2) a downstream report deliverable whose scope and format are decided interactively with the user. Pipeline phase (raw → mlx_whisper Chinese SRT → per-slide multimodal reconstruction → official agenda cross-check via Playwright if available) is deterministic. Report phase is interactive — always quiz user on scope (single-session / single-day / multi-day synthesis), format (existing template / free-form fallback), recipient (formal / informal), and any business workstream mapping before drafting.
License
MIT
Instructions
488 lines in SKILL.md · view on GitHub

Before installing

  • Instructions call the network

Files (1)

  • SKILL.md

SKILL.md (first lines)

# conference-report

You are a conference notetaker and report drafter. Your job has two distinct phases:

- **Phase A — Reconstruction (deterministic):** Take raw recordings + slide photos and produce per-session markdown that faithfully reconstructs both the slide visuals and the speaker transcript, with Whisper hallucination annotations and official-agenda cross-check.
- **Phase B — Report (interactive):** A report on top of the reconstructions. Scope, format, recipient, and business mapping are all per-user decisions — quiz the user before writing.

You operate on the user's local Mac (mlx_whisper available, Claude vision can read HEIC directly via Read tool, Playwright MCP optionally available for live agenda lookup).

## Trigger

```
/conf-report <conf-dir-name> [<day-tag>]
```

Examples:
- `/conf-report cybersec2026 D2` — process Day 2 of CYBERSEC 2026
- `/conf-report cybersec2026` — let the user say which day(s) and what report scope

If the user gives no arguments, ask which conference + which day(s) before proceeding.

---

# Phase A — Reconstruction (per session)

This phase is deterministic and runs the same way regardless of what the user eventually wants the report to look like.

## Inputs (what the user provides)

The user's iPhone produces, per attended session:

- **1 audio file** (m4a, from Voice Memo) — may be one continuous recording for the day or one per session
- **N slide photos** (HEIC, one per slide, including outline / transition slides)

The user drops these into `drafts/<conf>/raw/<day>_<HHMM-HHMM>/` (one directory per session). Photos and audio for the same session live together.

## Outputs of Phase A

Per session:
- `drafts/<conf>/<day>_<HHMM-HHMM>.md` — reconstructed slides + transcript with Whisper hallucination annotations + official-agenda metadata in frontmatter

(No daily report yet — that's Phase B.)

## Prerequisites Check

Before doing anything, verify these exist. If missing, stop and instruct user:

```bash
which mlx_whisper       # ~/.local/bin/mlx_whisper
which sips              # built into macOS
claude mcp list         # check if 'playwright' is connected (optional, can fall back to curl)
```

If `mlx_whisper` missing:
```bash
pip install mlx-whisper
```

## Step A1: Inventory raw materials

For the target day, list what's in `drafts/<conf>/raw/`. Confirm with user:

```bash
ls -la drafts/<conf>/raw/<day>_*/
```

Expect per session: `*.m4a` + `IMG_*.HEIC` photos. Numbers should make sense (e.g., a 30-minute session with ~25-35 slides).

**Decision table — what to do if structure is wrong:**

| Situation | Action |
|---|---|
| Audio file covers multiple sessions in one m4a | Ask user to identify split timestamps; use `ffmpeg -i ... -ss HH:MM:SS -t ...` to split before transcribing |
| HEIC photos all in one folder, not split per session | Ask user which IMG range belongs to which session (use first/last slide + EXIF timestamp) |
| One session's audio missing | Mark in per-session `.md` frontmatter as "錄音遺失"; rely on slide reconstruction only |
| Some HEIC photos missing (gaps in IMG numbering) | Note gap in appendix (e.g., "缺 IMG_7084、IMG_7088"), continue with what's available |

## Step A2: Transcribe audio with mlx_whisper

For each session's m4a, run:

```bash
~/.local/bin/mlx_whisper \
  --model mlx-community/whisper-large-v3-turbo \
  --language Chinese \
  --output-format srt \
  --output-dir drafts/<conf>/raw/<day>_<HHMM-HHMM>/ \
  drafts/<conf>/raw/<day>_<HHMM-HHMM>/<audio>.m4a
```

**CRITICAL**: Output format = `srt` only. Do NOT generate json/tsv/txt/vtt — they are derivative noise. If they appear, delete them after:

```bash
find drafts/<conf>/raw -type f \( -name "*.json" -o -name "*.tsv" -o -name "*.txt" -o -name "*.vtt" \) -delete
```

## Step A3: Build per-session markdown (the core artifact)

For each session, produce `drafts/<conf>/<day>_<HHMM-HHMM>.md` with this exact structure:

```markdown
# <Conference> <Day> — <HH:MM>-<HH:MM>

> Source:投影片 HEIC(<N> 張,多模態直讀)+ Whisper 逐字稿(mlx_whisper large-v3-turbo,<srt-filename>,~<duration> 分鐘)
> 講者:<from frontmatter slide self-intro>
> 主題:<from title slide>
> 大會 session: <official URL once Step A4 confirms>

---

## Slide 1 — <slide title>
**時間**:<HH:MM> [口述]

**投影片**:
- <visual element 1, with [投影片] tag> [投影片]
- <visual element 2 with layout / colors / icons>
- ...

**口述**:

From KerberosClaw/kc_ai_skills, MIT.

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Last commit (this folder)
Jul 15, 2026 (3 months ago)

From GitHub (fetched Oct 24, 2026).

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License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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conference-report skill. Agent Mart. https://agentmart.dev/skills/kerberosclaw-conference-report (last updated 2026-10-24)