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
Install
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.
npx agentmarket install skill/kerberosclaw-conference-report
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: documents, presentations, testing, data
Reviews
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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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- Install scripts
- None found
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**:
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Signals
- Stars
- 79
- Forks
- 14
- Open issues
- 0
- Last commit (this folder)
- Jul 15, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/KerberosClaw/kc_ai_skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
conference-report skill. Agent Mart. https://agentmart.dev/skills/kerberosclaw-conference-report (last updated 2026-10-24)