Claude Code Skills Marketplace is a collection and marketplace of skills, plugins, agents, and instructions that extend Claude Code with specialized development workflows. It is for developers who want to install existing workflows or create, validate, and package their own Claude Code skills.
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.
npx skills add daymade/claude-code-skills --skill asr-transcribe-to-textgit clone --depth 1 https://github.com/daymade/claude-code-skillsWrote 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.
[](https://agentmods.dev/skills/daymade/claude-code-skills/asr-transcribe-to-text)<a href="https://agentmods.dev/skills/daymade/claude-code-skills/asr-transcribe-to-text"><img src="https://agentmods.dev/badge/skills/daymade/claude-code-skills/asr-transcribe-to-text/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.
<a href="https://agentmods.dev/skills/daymade/claude-code-skills/asr-transcribe-to-text"><img src="https://agentmods.dev/badge/skills/daymade/claude-code-skills/asr-transcribe-to-text.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 843 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
- medium Excessive Agency · line 837 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00321 | $0.13639 |
| Opus 5 | $0.00161 | $0.06820 |
| Sonnet 5 | $0.00064 | $0.02728 |
| Haiku 4.5 | $0.00032 | $0.01364 |
Grade A, and why
asr-transcribe-to-text scanned grade A with 2 findings 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 4d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
['curl', '-s', '--max-time', '10'] + noproxy + [f'{base}/models'], Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run( How it starts
The opening of the file, as written. The whole thing — 1,029 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ASR Transcribe to Text
Transcribe audio/video to speaker-labeled text. Local execution has two explicit routes. Long or unattended recordings use checkpointed whisper.cpp + Silero VAD blocks, then late-fuse pyannote speakers. Short/medium recordings may use the Qwen3-ASR + mlx-whisper alignment route. Neither route cuts ASR input at diarization turns; speaker attribution happens after continuous-context ASR.
Route before ASR: the transcript is the result, not the run
Before starting transcription, check the owning project's transcript catalog, external source index, and declared prior-work carriers for an existing canonical transcript using source ID, date, title, and entity terms. A verified human-reviewed/current transcript ends the task unless the user explicitly asked for a new independent comparison. Raw audio existing is not a reason to regenerate text that already exists.
When no canonical transcript exists:
- For ordinary meeting/DJI recordings where cloud processing is allowed, use Feishu Minutes as the normal primary route (preprocess to a small M4A first).
- Use local ASR when the user requires offline/privacy handling, Feishu is unavailable or failed, or the task explicitly needs an independent quality comparison.
- For non-meeting media or an explicit local/remote ASR request, choose the execution location by the audio-location rule below.
Do not run local ASR merely to make a two-route process look complete.
| Mode | When | Speed | Cost |
|---|---|---|---|
| Local MLX | macOS Apple Silicon | 15-27x realtime | Free |
| Remote API | Any platform, or when local unavailable | Depends on GPU | API/self-hosted |
Choosing between them is usually not about speed — it's about where the audio already is. A remote GPU can be several times faster (a 4090 running vLLM measured ~61x realtime against ~15x for local MLX), but that gap is small change next to moving the files: transcription output is text, and text is ~10,000× smaller than the audio it came from (18.5 h of speech ≈ 330 K characters ≈ 1 MB, from ~2.6 GB of WAV). So:
What ships with it
29 files 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.
- .gitignore 104 B
- references/decoupled_speaker_alignment.md 7.9 KB
- references/local_mlx_guide.md 8.3 KB
- references/overlap_merge_strategy.md 3.6 KB
- references/speaker_diarization.md 6.5 KB
- references/voiceprint_speaker_id.md 4.7 KB
- references/whisper_word_timestamps.md 3.7 KB
- scripts/align_speakers.py 14 KB runs code
- scripts/diarize_speakers.py 13 KB runs code
- scripts/diarize_speakers.py.lock 212 KB
- scripts/fuse_whispercpp_diarization.py 27 KB runs code
- scripts/generate_audit_html.py 79 KB runs code
- scripts/overlap_merge_transcribe.py 8.9 KB runs code
- scripts/prepare_asr_input.py 8.2 KB runs code
- scripts/resolve_media_input.py 18 KB runs code
- scripts/speaker_time_contract.py 1.3 KB runs code
- scripts/speaker_transcribe_cascade.py 6.9 KB runs code
- scripts/speaker_transcribe.py 39 KB runs code
- scripts/speaker_transcribe.py.lock 212 KB
- scripts/transcribe_local_mlx.py 30 KB runs code
- scripts/transcribe_long_whispercpp.py 29 KB runs code
- scripts/voiceprint_id.py 9.4 KB runs code
- scripts/word_timestamps_whisper.py 4.1 KB runs code
- tests/test_alignment_turns.py 7.8 KB runs code
- tests/test_long_audio_safety.py 48 KB runs code
- tests/test_skill_delivery_contract.py 1.9 KB runs code
- tests/test_speaker_bundle_time_contract.py 4.7 KB runs code
- tests/test_whispercpp_fusion.py 9.4 KB runs code
- tests/test_whispercpp_long_audio.py 4.6 KB runs code
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.
- 4d ago Changed · +19 lines c2b3d2955521
- 8d ago Changed · +41 lines 606c04b6e0dc
- 11d ago First seen · 969 lines · 321 tokens per session scan A df2865ad8353
asr-transcribe-to-text is a skill published in the GitHub repository daymade/claude-code-skills (1,387 stars, last pushed today), licensed MIT. It adds 321 tokens to every session and 13,639 once invoked, about $0.0016 per session on Opus 5. A static security scan graded it A with 2 findings (makes network calls, 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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