PyTheory is a Python toolkit for exploring music theory and composing music, with immediate audio playback and visual representations such as guitar tabs and chord diagrams. Musicians and programmers use it to create arrangements across multiple musical systems, instruments, rhythms, and effects. The catalogue add-ons provide agent guidance for working with the project.
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 kennethreitz/pytheory --skill chord-lab-with-pytheorygit clone --depth 1 https://github.com/kennethreitz/pytheoryWrote 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/kennethreitz/pytheory/chord-lab-with-pytheory)<a href="https://agentmods.dev/skills/kennethreitz/pytheory/chord-lab-with-pytheory"><img src="https://agentmods.dev/badge/skills/kennethreitz/pytheory/chord-lab-with-pytheory/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/kennethreitz/pytheory/chord-lab-with-pytheory"><img src="https://agentmods.dev/badge/skills/kennethreitz/pytheory/chord-lab-with-pytheory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00114 | $0.02231 |
| Opus 5 | $0.00057 | $0.01115 |
| Sonnet 5 | $0.00023 | $0.00446 |
| Haiku 4.5 | $0.00011 | $0.00223 |
Grade A, and why
chord-lab-with-pytheory 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 11d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- chord-lab-with-pytheory — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chord Lab
Everything about a single chord — construction, voicing, and analysis.
Build a chord
from pytheory import Chord
Chord.from_symbol("F#m7b5") # widest parser: sus, add9, alterations, slash
Chord.from_name("Am") # plain names (major/minor/7/maj7/dim/…)
Chord.from_intervals("C", 0, 4, 7) # root + semitone intervals
Chord.from_tones("C", "E", "G") # explicit notes
A Chord has .symbol, .tones (list of Tone), .root, and
.transpose(semitones).
Voicings
inversion, drop2, drop3, and open_voicing return a new Chord. The
chord symbol stays the same — the change is in the tones (order/octave), so
inspect .tones:
c = Chord.from_symbol("Cmaj7")
[str(t) for t in c.tones] # ['C4', 'E4', 'G4', 'B4']
[str(t) for t in c.inversion(1).tones] # ['E4', 'G4', 'B4', 'C5']
[str(t) for t in c.drop2().tones] # ['G3', 'C4', 'E4', 'B4']
[str(t) for t in c.open_voicing().tones] # ['C4', 'E5', 'G4', 'B5']
drop3() exists too. Use these to spread a close voicing for piano/strings/guitar.
Analysis
c = Chord.from_symbol("Cmaj7")
c.intervals # [4, 3, 4] semitone steps between stacked tones
c.pitch_classes # {0, 4, 7, 11}
c.forte_number # '4-20' set-theory label
c.figured_bass # '7'
c.extensions() # [<Tone D5>, <Tone A5>] available 9/11/13 tones
c.tension # {'score': 0.15, 'tritones': 0, 'minor_seconds': 1,
# 'has_dominant_function': False}
c.dissonance # 5.33 (a roughness number; higher = more dissonant)
c.beat_frequencies # [(Tone, Tone, hz), …] beating between pairs in ET
Pitch-class-set toolkit
c = Chord.from_symbol("Cmaj7")
c.normal_form # (11, 0, 4, 7) most compact ordering
c.prime_form # (0, 1, 5, 8) canonical set-class form
c.interval_vector # (1, 0, 1, 2, 2, 0) interval-class content <ic1..ic6>
c.complement # Chord of the other 8 pitch classes
# Set-class relationships between two chords:
Chord.from_symbol("C").is_transposition_of(Chord.from_symbol("G")) # True (Tn)
Chord.from_symbol("C").is_set_class_equivalent(Chord.from_symbol("Cm")) # True (TnI: maj/min)
Chord.from_symbol("C").is_subset_of(Chord.from_symbol("Cmaj7")) # True
# Z-relation — same interval vector, different set class (e.g. 4-z15 / 4-z29):
a, b = Chord.from_midi_message(0,1,4,6), Chord.from_midi_message(0,1,3,7)
a.is_z_related(b) # True
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.
- 11d ago First seen · 178 lines · 114 tokens per session scan A efe7f258946c
chord-lab-with-pytheory is a skill published in the GitHub repository kennethreitz/pytheory (1,639 stars, last pushed 1mo ago), licensed MIT. It adds 114 tokens to every session and 2,231 once invoked, about $0.0006 per session on Opus 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 2026-08-30.
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