bass-transcribe

bass-transcribe is a skill for Claude Code, Codex from PerIPan/music-workflow-skills. It costs 42 tokens per session (2,230 once invoked), scanned A, original, MIT.

A workflow for turning a recorded bass or other single-note instrument performance into MIDI, an Ableton Live clip, or written tablature or notation. MIDI is editable musical note data, and a monophonic performance uses one note at a time.

In plain words
What is it for?
Transcribing bass recordings, handling double-stops when needed, and cleaning up and segmenting detected notes.
Why use it?
It helps convert an audio take into editable notes instead of requiring the player to transcribe the performance by hand.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Transcribing bass recordings, handling double-stops when needed, and cleaning up and segmenting detected notes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/peripan/music-workflow-skills/bass-transcribe
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 PerIPan/music-workflow-skills --skill bass-transcribe
Clone the repo
git clone --depth 1 https://github.com/PerIPan/music-workflow-skills

Made for: Claude Code, Codex.

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 bass-transcribe

README.md
[![agentmods](https://agentmods.dev/badge/skills/peripan/music-workflow-skills/bass-transcribe/github.svg)](https://agentmods.dev/skills/peripan/music-workflow-skills/bass-transcribe)
Your own site
<a href="https://agentmods.dev/skills/peripan/music-workflow-skills/bass-transcribe"><img src="https://agentmods.dev/badge/skills/peripan/music-workflow-skills/bass-transcribe/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 bass-transcribe

Your own site · 80×15
<a href="https://agentmods.dev/skills/peripan/music-workflow-skills/bass-transcribe"><img src="https://agentmods.dev/badge/skills/peripan/music-workflow-skills/bass-transcribe.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,230 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00042 $0.02230
Opus 5.5 $0.00017 $0.00892
Sonnet 5.5 $0.00008 $0.00446
Haiku 4.5 $0.00004 $0.00223

Measured 1mo ago against content hash 97095ddd1074, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

bass-transcribe scanned grade A with 0 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 1mo 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

bass-transcribe/SKILL.md · 150 lines

How it starts

The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Bass Transcribe — played take → MIDI / Live clip / chart

Default for bass is the offline pyin pipeline. For vocals and expressive leads (sax, synth lead) switch to CREPE (§2b). For in-Live plugin options (NeuralNote, Jam Origin) read references/realtime-options.md.

Why pyin, not CREPE, for bass: in a side-by-side A/B in Live on a separated bass stem, the CREPE line was rejected by ear ("CREPE is not for bass") — it over-segments a slow-moving line into spurious adjacent notes. Published evidence agrees: pYIN beats CREPE on bass lines because CREPE's training set has almost no sub-bass examples (Araz, ISMIR 2021 LBD), and no public pitch benchmark covers the bass register. pyin is also ~30× faster. On vocals the same A/B went the other way — CREPE caught quiet, legato notes pyin dropped.

1. Get the audio

  • User points at a file — wav/mp3/aiff of the take. Mono preferred; DI cleaner than mic.
  • Record in Live — audio track, arm, record the take. MCP cannot export audio: the user does File → Export, or point at the raw recording under the Set's Samples/Recorded/ folder.
  • Ask for (or detect) the take's BPM if the output will go into a Live clip.

2. Default pipeline — pyin → MIDI

import librosa, numpy as np, pretty_midi

y, sr = librosa.load(AUDIO, sr=22050, mono=True)
HOP = 256                                                    # 11.6 ms
f0, voiced, vprob = librosa.pyin(y, sr=sr, fmin=40.0, fmax=220.0,   # E1 … A3
                                 frame_length=4096, hop_length=HOP)
t = librosa.times_like(f0, sr=sr, hop_length=HOP)
rms = librosa.feature.rms(y=y, frame_length=4096, hop_length=HOP)[0]
rms = rms / (rms.max() + 1e-9)

VPROB, MIN_LEN, GAP = 0.55, 0.10, 0.05   # voicing gate, min note s, bridgeable dropout s
pitch = np.where(voiced & (vprob >= VPROB),
                 np.round(librosa.hz_to_midi(np.nan_to_num(f0, nan=40.0))), -1).astype(int)
notes, cur = [], None
for i, (ti, p) in enumerate(zip(t, pitch)):
    if cur and p == cur['p']:
        cur['end'], cur['i1'] = ti, i                        # same pitch: extend
        continue
    if cur and p < 0 and ti - cur['end'] <= GAP:
        continue                                             # short dropout: bridge it
    if cur and cur['end'] - cur['start'] >= MIN_LEN:
        notes.append(cur)                                    # pitch change / long gap: close
    cur = {'p': p, 'start': ti, 'end': ti, 'i0': i, 'i1': i} if p >= 0 else None
if cur and cur['end'] - cur['start'] >= MIN_LEN:
    notes.append(cur)

pm = pretty_midi.PrettyMIDI()
inst = pretty_midi.Instrument(program=33)                    # Electric Bass (finger)
for n in notes:
    vel = int(np.clip(50 + 70 * rms[n['i0']:n['i1'] + 1].mean(), 35, 120))
    inst.notes.append(pretty_midi.Note(velocity=vel, pitch=n['p'],
                                       start=n['start'], end=n['end']))
pm.instruments.append(inst)
pm.write(OUT_MID)

Read the full file on GitHub · 150 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. 1mo ago Changed · +59 lines · -39 tokens per session 97095ddd1074
  2. 2mo ago First seen · 91 lines · 81 tokens per session scan A 62a3418bc870

Subscribe to this mod's changes

bass-transcribe is a skill published in the GitHub repository PerIPan/music-workflow-skills (3 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 2,230 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

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