Bitterbot is a local-first personal AI agent that runs on a user’s devices, keeps persistent memories, performs tasks, and can exchange reusable skills with other agents. It is intended for people who want a personal assistant that remains available across conversations and activities. The catalogue entries provide instructions and agents for working with Bitterbot.
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 Bitterbot-AI/bitterbot-desktop --skill songseegit clone --depth 1 https://github.com/Bitterbot-AI/bitterbot-desktopWrote 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/bitterbot-ai/bitterbot-desktop/songsee)<a href="https://agentmods.dev/skills/bitterbot-ai/bitterbot-desktop/songsee"><img src="https://agentmods.dev/badge/skills/bitterbot-ai/bitterbot-desktop/songsee/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/bitterbot-ai/bitterbot-desktop/songsee"><img src="https://agentmods.dev/badge/skills/bitterbot-ai/bitterbot-desktop/songsee.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00020 | $0.00369 |
| Opus 5 | $0.00010 | $0.00185 |
| Sonnet 5 | $0.00004 | $0.00074 |
| Haiku 4.5 | $0.00002 | $0.00037 |
Grade A, and why
songsee 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 13d 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.
This is a copy
98% identical to songsee — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
songsee
Generate spectrograms + feature panels from audio.
Quick start
- Spectrogram:
songsee track.mp3 - Multi-panel:
songsee track.mp3 --viz spectrogram,mel,chroma,hpss,selfsim,loudness,tempogram,mfcc,flux - Time slice:
songsee track.mp3 --start 12.5 --duration 8 -o slice.jpg - Stdin:
cat track.mp3 | songsee - --format png -o out.png
Common flags
--vizlist (repeatable or comma-separated)--stylepalette (classic, magma, inferno, viridis, gray)--width/--heightoutput size--window/--hopFFT settings--min-freq/--max-freqfrequency range--start/--durationtime slice--formatjpg|png
Notes
- WAV/MP3 decode native; other formats use ffmpeg if available.
- Multiple
--vizrenders a grid.
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.
- 13d ago First seen · 50 lines · 20 tokens per session scan A 7adab2990fec
songsee is a skill published in the GitHub repository Bitterbot-AI/bitterbot-desktop (2,462 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 369 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to songsee, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
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emem-recall-polygon
Recall signed Earth-observation facts at every cell inside a user-supplied polygon. Use when the user asks about an extent rather than a point — "what's the average NDVI inside this watershed", "show me precipitation across the Western Ghats", "what's the elevation profile of this region". Accepts a polygon as [lng…
emem-locate-and-recall
Resolve a free-form place name to an emem cell64 and recall signed Earth-observation facts at that location. Use when the user asks about current weather, vegetation index, elevation, soil properties, or any other geospatial measurement at a named place ("what's the temperature in Bengaluru", "how high is Denali"…
maps-geography
Accurate maps from real geo data — use for any map, or whenever geography would make a good graphic for a deliverable.
python-math
Small Python utilities for math and text files.
arxiv-search
Search and retrieve scientific papers from ArXiv.