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 keys-and-harmony-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/keys-and-harmony-with-pytheory)<a href="https://agentmods.dev/skills/kennethreitz/pytheory/keys-and-harmony-with-pytheory"><img src="https://agentmods.dev/badge/skills/kennethreitz/pytheory/keys-and-harmony-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/keys-and-harmony-with-pytheory"><img src="https://agentmods.dev/badge/skills/kennethreitz/pytheory/keys-and-harmony-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 | $0.00132 | $0.01881 |
| Opus 5 | $0.00066 | $0.00941 |
| Sonnet 5 | $0.00026 | $0.00376 |
| Haiku 4.5 | $0.00013 | $0.00188 |
Grade A, and why
keys-and-harmony-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:
- keys-and-harmony-with-pytheory — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Keys & Harmony
Working with keys and progressions — the harmonic level above a single chord.
Keys and their diatonic content
from pytheory import Key
k = Key("C", "major")
k.chords # ['C major', 'D minor', 'E minor', 'F major', 'G major', 'A minor', 'B diminished']
k.seventh_chords # ['C major 7th', 'D minor 7th', …, 'G dominant 7th', …]
k.note_names # ['C', 'D', 'E', 'F', 'G', 'A', 'B', 'C']
k.signature # {'sharps': 0, 'flats': 0, 'accidentals': []}
k.relative # <Key A minor>
Detect the key
Key.detect("C", "E", "G", "B", "D") # -> <Key C major>
Progressions
k = Key("G", "major")
[c.symbol for c in k.progression("I", "V", "vi", "IV")] # ['G', 'D', 'Em', 'C']
[c.symbol for c in k.nashville(1, 5, 6, 4)] # ['G', 'D', 'Em', 'C']
k.random_progression(4) # a diatonic [Chord, …]
Roman-numeral analysis of an existing progression:
from pytheory import analyze_progression, Chord
chords = [Chord.from_symbol(s) for s in ["C", "G", "Am", "F"]]
analyze_progression(chords, key="C", mode="major") # ['I', 'V', 'vi', 'IV']
Secondary dominants — applied dominants that tonicise a non-tonic
degree. detect_secondary_dominant identifies one chord (the analytical
inverse of Key.secondary_dominant(degree), which builds one); pass
secondary_dominants=True to analyze_progression to label them in
context (instead of the bare degree):
from pytheory import detect_secondary_dominant, analyze_progression, Chord
detect_secondary_dominant(Chord.from_symbol("D7"), "C") # 'V7/V' (D7 -> G)
detect_secondary_dominant(Chord.from_symbol("E7"), "C") # 'V7/vi' (E7 -> Am)
prog = [Chord.from_symbol(s) for s in ("C", "D7", "G7", "C")]
analyze_progression(prog, "C", secondary_dominants=True) # ['I', 'V7/V', 'V7', 'I']
From the terminal, pytheory analyze C D7 G7 C prints the whole picture —
detected key, Roman numerals (with secondary dominants), and cadences
(add --key/--mode to fix the key).
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 · 158 lines · 132 tokens per session scan A 173ba7c691a5
keys-and-harmony-with-pytheory is a skill published in the GitHub repository kennethreitz/pytheory (1,639 stars, last pushed 1mo ago), licensed MIT. It adds 132 tokens to every session and 1,881 once invoked, about $0.0007 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.
Other skills, from other repositories
music-composition
Use this skill whenever the user asks for help with music composition, music theory, songwriting, harmony, melody, counterpoint, arrangement, orchestration, or musical analysis — across classical, jazz, pop, rock, hip-hop, R&B, electronic, film/TV, K-pop/J-pop, folk, or musical theatre. Triggers include explicit…
html-ppt-zhangzara-daisy-days
A customer-success workshop onboarding users to a project-management app — the first-value path and the habits that retain. Built as a decision-grade professional training deck for new customers, CS team.
html-ppt-zhangzara-retro-windows
An IT security-awareness training on spotting phishing — the tells, the drill, and what to do in the first 60 seconds. Built as a decision-grade professional training deck for all employees.
sprite-animation
A pixel / sprite-style animated explainer slide — full-bleed cream stage, bold display year, animated pixel-art mascot (e.g. Hanafuda card, mushroom, or 8-bit console), kinetic Japanese display type, ticking timeline ribbon. Reads like a single frame of an educational motion video — looping CSS keyframes, no JS, ready…
baoyu-comic
A tool for creating original educational comics that explain knowledge or ideas through multiple illustrated panels. It supports different art styles and tones and can create several comics in one batch.
animation
Author animated technical explainer diagrams as .anim.json files for Nimbalyst's Animation editor. Use when the user wants to animate a diagram, show how a system/protocol/algorithm behaves over time, build a motion explainer, or turn a static architecture diagram into something that plays.