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 agentmods add instructions/learningtour/chat-with-audio/claude-mdgit clone --depth 1 https://github.com/learningtour/chat-with-audioWrote 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/instructions/learningtour/chat-with-audio/claude-md)<a href="https://agentmods.dev/instructions/learningtour/chat-with-audio/claude-md"><img src="https://agentmods.dev/badge/instructions/learningtour/chat-with-audio/claude-md.svg" alt="Measured on agentmods" 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 | $0.01635 | $0.01635 |
| Opus 5 | $0.00817 | $0.00817 |
| Sonnet 5 | $0.00327 | $0.00327 |
| Haiku 4.5 | $0.00163 | $0.00163 |
Grade A, and why
chat-with-audio CLAUDE.md 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 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.
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.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chat with Audio — development notes
Chat-driven audio enhancement tool: MCP server (FastMCP, stdio) + C++ DSP core (pybind11) + local A/B viewer. See README.md and docs/ for user documentation (tool reference, workflows, compliance, smart regions, recipes, architecture).
Name everywhere: Chat with Audio (package
chat_with_audio, MCP serverchat-with-audio, GitHubchat-with-audio, local project folder "Chat with Audio").
Commands
uv sync --all-extras # build (incl. C++) + all deps
uv sync --reinstall-package chat-with-audio # after changes in cpp/
uv run pytest # test suite
uv run ruff check . # lint (also runs in CI)
uv run python scripts/mcp_smoke.py # MCP stdio smoke test
uv run ait analyze <file> # dev CLI without MCP
uv run ait improve <file> [--profile speech|music] [--denoise-method ai]
uv run ait viewer # viewer on :8471
Architecture map
cpp/— header-only DSP (biquad.hpp, dynamics.hpp) +bindings.cpp→ modulechat_with_audio._dsp. Arrays are float32 (channels, n); functions return new arrays; dynamics use a linked detector across channels.src/chat_with_audio/dsp/__init__.py— dispatch: native_dspwhen built, otherwisefallback.py(scipy; identical signatures, block-based dynamics).spectral_nr.py= Tier A denoise;ai_nr.py= Tier B (DeepFilterNet).analysis.py→ metrics dict +score_and_issues();improve.py→ profile detection + rules → (steps, rationale);chain.py→STEP_REGISTRY+ execution (incl.levelerand segment-drivensmart_denoise).regions.py→ smart problem regions: windowed detectors (hum/noise/clip/boom) find where on the timeline something is wrong; per-region mini-chains are applied with raised-cosine crossfades, everything outside stays untouched (smart_edittool). Noise reference floor is clamped to -80 dB; boom regions inside a hum region are dropped (the notch already covers them).recipes.py→ saved chains as shareable JSON (save_recipe/apply_recipe/list_recipes); built-ins live insrc/chat_with_audio/recipes/, user recipes in~/AudioImprove/recipes/(envAIT_RECIPES_DIR; tests isolate this automatically).chain.validate_steps()guards every load/save.segments.py→ speech/music/silence segmentation (level-Otsu primary; modulation rhythm as fallback).refine.py→ iterative measure-and-adjust loop (refine_audiotool): AI denoising once up front, then adjust leveler/loudness until the speech peak and balance are right; silence segments are pushed back down afterwards (_duck_silence) because the leveler would otherwise lift them.compliance.py→ delivery-spec registry (EBU R128, ATSC A/85, Netflix 2.0 én 5.1 dialogue-gated, streaming, ACX) + pass/fail checker incl. formaat- en kanaaleisen;master_forschrijft compliance.json (viewer-paneel) en exporteert mono → dual-mono bij een 2.0-eis. dialogue_loudness = blok- gebaseerde spraak-gated meting (DI-achtig, niét het Dolby-algoritme); op 5.1 detectie op het centerkanaal.- Surround:
SURROUND_LAYOUTSin analysis.py — 5.1 (SMPTE) krijgt gewogen BS.1770 (LFE eruit via loudness_view), per-kanaal-QC en ITU-downmix-piek; ADM BWF (Atmos-metadata) wordt herkend via axml/chna-chunks in io.probe. dsp/dialogue.py→ breath_control / deplosive / duck_music (chain steps); gain envelopes are smoothed with edge padding — plain convolution would drag file edges toward zero.markers.py→ region map → Audition marker CSV + Audacity labels + JSON (export_markers).dsp/roomtone.py→ room-tone fill: digitale gaten vullen met geshuffelde overlap-add van de eigen ambience (fill_room_tone);qcsheet.py→ markdown-QC-rapport (qc_report, batch:qc_folder).dsp/spectral_repair.py→ spectral painting (spectral_repair): magnitudes interpoleren uit de context, fase phase-vocoder-coherent voortzetten (bin-centerfrequenties laten mainlobe-bins driften — gemeten dphi gebruiken).duck_musicheeft twee modi: beds (segmentniveau, licht) en stems (Demucs-sidechain voor muziek ónder spraak, [stems]-extra).sync.py→ 32-sporenrecorder (sync_tracks): envelope-GCC-PHAT + full-rate verfijning, confidence per spoor, klokdrift-meting/-correctie; uitgelijnde wavs + .sesx; A/B-sessie = ongesynct vs gesynct mixdown. Valkuil: strak periodiek materiaal (metronoom) is inherent dubbelzinnig voor correlatie — testsignalen moeten aperiodiek gaten (en recorder-seeds ver van event-seeds, anders ontstaat een echte schijncorrelatie).server.py— 30 MCP tools;sessions.py— session folders under~/AudioImprove/sessions/(envAIT_SESSIONS_DIR; tests isolate this automatically). Every session writestimeline.json(segments + treated regions) for the viewer's timeline lane; ids get a-2suffix on collision.viewer/server.py— stdlib http.server on 127.0.0.1:8471 (envAIT_VIEWER_PORT);viewer/static/app.js— A/B player: both buffers always play together, switching = gain crossfade.
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 First seen · 98 lines · 1,635 tokens per session scan A 4b351a18029a
chat-with-audio CLAUDE.md is an instructions file published in the GitHub repository learningtour/chat-with-audio (1 stars, last pushed 1mo ago), licensed MIT. It adds 1,635 tokens to every session, about $0.0082 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 2026-08-31.
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