Remove the debug mode and simplify the detection path

.gitignore

@@ -14,3 +14,6 @@ tmp/
 # Python
 __pycache__/
 *.pyc
+
+# Local agent notes
+CLAUDE.local.md

AGENTS.md

@@ -1,5 +1,5 @@
-strict no backward compatibility no matter what, so feel free to make breaking changes as needed. Just make sure to
-do `cargo clippy --all-targets -- -D warnings` after changes to make sure code style is correct and then `cargo test` as needed.
+- strict no backward compatibility or legacy code paths no matter what, no change logs either.
+- do `cargo clippy --all-targets -- -D warnings` after changes and then `cargo test` as needed.
 
 - Use `./tmp` as the temporary working directory for debug output, scratch files, etc. It is gitignored.
 - The project is a Cargo workspace: `crates/core` (`audio-pattern-detector-core`, the library) and `crates/cli` (`audio-pattern-detector`, the binary). Keep CLI-only dependencies (e.g. clap) out of the core crate. See `docs/development.md` for the code layout.
@@ -21,9 +21,8 @@ do `cargo clippy --all-targets -- -D warnings` after changes to make sure code s
 
 ## Debugging opus/lossy audio
 
-- Use `--debug` and `--debug-dir <dir>` to save debug output per run. Use separate debug dirs for A/B comparisons.
-- Debug graphs are not implemented yet (planned for v2, see `docs/roadmap.md`). Until then use the stderr diagnostics and the per-section peak dumps in `debug/cross_correlation_<clip>/`, which contain the MSE similarity and per-window Pearson r of every candidate.
-- Debug audio sections in `audio_section/` can be listened to for ground truth verification. Don't assume old detection results are correct.
+- There is no debug mode yet (planned for v2, see `docs/roadmap.md`).
+- Listen to the audio around a candidate for ground truth verification. Don't assume old detection results are correct.
 - Pattern clips should be extracted from the same encoding as the target audio (e.g. from an Opus stream when matching Opus audio). Denoise as a fallback when source-matched clips aren't available. See `docs/denoise-strategy.md`.
 
 ## Version bumping

Cargo.toml

@@ -3,7 +3,7 @@ resolver = "2"
 members = ["crates/core", "crates/cli"]
 
 [workspace.package]
-version = "0.4.3"
+version = "0.4.4"
 edition = "2021"
 authors = ["Andrew Chen <hello@andrewtheguy.com>"]
 

README.md

@@ -4,7 +4,7 @@ Detects audio patterns specified by audio clips in target audio files. Designed
 
 Useful for AI workflows to efficiently segment audio files before processing (e.g., OpenAI Whisper transcription preprocessing).
 
-Detection is a two-step process. **Step 1** always runs FFT cross-correlation against the audio to find and center potential match locations. **Step 2** verifies each candidate using one of three paths chosen by clip type: normal verification (partitioned MSE + multi-window Pearson correlation), short-clip verification (single-window variant for clips under 0.5s), or marker-tone verification (narrowband spectral check for `.apd.toml` patterns like station beeps). Robust against lossy-encoded audio (Opus, AAC).
+Detection is a two-step process. **Step 1** always runs FFT cross-correlation against the audio to find and center potential match locations. **Step 2** verifies each candidate using one of three paths chosen by clip type: normal verification (partitioned MSE + center-window Pearson correlation), short-clip verification (single-window variant for clips under 0.5s), or marker-tone verification (narrowband spectral check for `.apd.toml` patterns like station beeps). Robust against lossy-encoded audio (Opus, AAC).
 
 Written in Rust: a single self-contained binary with no runtime dependencies (ffmpeg is only needed for non-WAV input files). Also available as a Python package with the same detector ([Python bindings](docs/python.md)).
 
@@ -25,7 +25,7 @@ cargo install --git https://github.com/andrewtheguy/audio_pattern_detector.git -
 `ghcr.io/andrewtheguy/audio_pattern_detector:<tag>` is published with each release (`v<version>`, plus `latest` for releases from `main`). It contains only the binary at `/usr/local/bin/audio-pattern-detector` (no ffmpeg), so the usual use is copying it into another image:
 
 ```dockerfile
-COPY --from=ghcr.io/andrewtheguy/audio_pattern_detector:v0.4.3 /usr/local/bin/audio-pattern-detector /usr/local/bin/audio-pattern-detector
+COPY --from=ghcr.io/andrewtheguy/audio_pattern_detector:v<version> /usr/local/bin/audio-pattern-detector /usr/local/bin/audio-pattern-detector
 ```
 
 The release workflow builds the image for amd64 and arm64 from the binaries it has already compiled (`runtime-prebuilt` target). To build it locally from source for the host architecture: `docker build --target runtime -t audio-pattern-detector .`
@@ -93,8 +93,6 @@ audio-pattern-detector show-config ./clips/rthk_beep.apd.toml
 | `--chunk-seconds`      | Seconds per chunk (default: 60, or "auto")                               |
 | `--timestamp-format`   | JSONL timestamp fields: `both` (default), `ms`, or `formatted`           |
 | `--height-min`         | Minimum correlation peak height (default: 0.25; lower to find weak matches) |
-| `--debug`              | Enable debug mode (diagnostics, candidate audio, peak dumps; no charts yet) |
-| `--debug-dir`          | Base directory for debug output (default: ./tmp)                         |
 
 ## JSONL Output Format
 
@@ -136,8 +134,8 @@ For custom audio sources, implement `SampleSource` and drive `AudioPatternDetect
 - **[Denoise Strategy](docs/denoise-strategy.md)** - How to denoise pattern clips for better matching with lossy-encoded or noisy audio
 - **[Python Bindings](docs/python.md)** - Python API, installation and building the wheel
 - **[Stdin Modes](docs/stdin-modes.md)** - WAV stdin and multiplexed stdin (IPC) with a Node.js example
-- **[Development](docs/development.md)** - Building, linting, testing, code layout, debug output
-- **[Roadmap](docs/roadmap.md)** - What v1 covers and the plan for debug charts in v2
+- **[Development](docs/development.md)** - Building, linting, testing, code layout
+- **[Roadmap](docs/roadmap.md)** - The plan for the debug mode and its charts in v2
 
 ## Development
 

audio_pattern_detector.pyi

@@ -41,8 +41,6 @@ class Detector:
         seconds_per_chunk: int | None = 60,
         target_sample_rate: int = 8000,
         height_min: float | None = None,
-        debug: bool = False,
-        debug_dir: StrPath = "./tmp",
     ) -> Detector: ...
     @property
     def clip_names(self) -> list[str]: ...

crates/cli/src/main.rs

@@ -71,14 +71,6 @@ struct MatchArgs {
     #[arg(long, value_name = "SECONDS", default_value = "60")]
     chunk_seconds: String,
 
-    /// Debug mode: diagnostics on stderr plus candidate audio and peak dumps under --debug-dir
-    #[arg(long)]
-    debug: bool,
-
-    /// Base directory for debug output
-    #[arg(long, value_name = "DIR", default_value = "./tmp")]
-    debug_dir: PathBuf,
-
     /// Override minimum correlation peak height (default: 0.25, lower to find weak matches)
     #[arg(long, value_name = "HEIGHT")]
     height_min: Option<f32>,
@@ -158,10 +150,8 @@ fn cmd_match(args: MatchArgs) -> Result<()> {
     };
 
     let options = MatchOptions {
-        debug_mode: args.debug,
         seconds_per_chunk,
         target_sample_rate: args.target_sample_rate,
-        debug_dir: args.debug_dir,
         height_min: args.height_min,
     };
 

crates/cli/tests/cli_integration.rs

@@ -8,7 +8,6 @@
 //! Internal detection logic is tested in the other integration test files.
 
 use std::collections::BTreeSet;
-use std::fs;
 use std::io::Write;
 use std::process::{Command, Output, Stdio};
 
@@ -30,9 +29,6 @@ const CBS_NEWS_CLIP_NAME: &str = "cbs_news";
 const RAINBOW_INTRO_PATTERN: &str = "../../sample_audios/clips/天空下的彩虹intro.wav";
 const PATTERN_FOLDER: &str = "../../sample_audios/clips";
 const NONEXISTENT_FILE: &str = "nonexistent.wav";
-/// Pattern name that would escape the debug directory if used as a path.
-const TRAVERSAL_CLIP_NAME: &str = "../../escape";
-const TRAVERSAL_SAFE_NAME: &str = ".._.._escape";
 const DEFAULT_SAMPLE_RATE: u32 = 8000;
 
 struct CliResult {
@@ -612,29 +608,3 @@ fn multiplexed_stdin_requires_no_pattern_file() {
     let result = run_cli_stdin(&["match", "--multiplexed-stdin"], payload);
     assert_eq!(result.code, 0);
 }
-
-#[test]
-fn multiplexed_stdin_debug_output_stays_inside_debug_dir() {
-    let pattern_data = fs::read(CBS_NEWS_PATTERN).unwrap();
-    let audio_data = fs::read(CBS_NEWS_AUDIO).unwrap();
-    let payload = build_multiplexed_payload(&[(TRAVERSAL_CLIP_NAME, &pattern_data)], &audio_data);
-
-    let root = tempfile::tempdir().unwrap();
-    let debug_dir = root.path().join("nested").join("debug_out");
-    let result = run_cli_stdin(&["match", "--multiplexed-stdin", "--debug", "--debug-dir", debug_dir.to_str().unwrap()], payload);
-    assert_eq!(detected_clip_names(&result.events()), BTreeSet::from([TRAVERSAL_CLIP_NAME.to_string()]));
-
-    // Everything written under the temp root is inside debug_dir, in
-    // directories named after the sanitised clip name.
-    let mut top_level: Vec<String> =
-        fs::read_dir(root.path()).unwrap().map(|e| e.unwrap().file_name().to_string_lossy().into_owned()).collect();
-    top_level.sort();
-    assert_eq!(top_level, vec!["nested".to_string()]);
-    let nested: Vec<String> = fs::read_dir(root.path().join("nested"))
-        .unwrap()
-        .map(|e| e.unwrap().file_name().to_string_lossy().into_owned())
-        .collect();
-    assert_eq!(nested, vec!["debug_out".to_string()]);
-    assert!(debug_dir.join("audio_section").join(TRAVERSAL_SAFE_NAME).is_dir());
-    assert!(debug_dir.join("debug").join(format!("cross_correlation_{TRAVERSAL_SAFE_NAME}")).is_dir());
-}

crates/core/Cargo.toml

@@ -22,8 +22,8 @@ pyo3 = { version = "0.28", optional = true, features = ["abi3-py39"] }
 realfft = "3.5"
 rustfft = "6.4"
 serde.workspace = true
-serde_json.workspace = true
 toml = "1.1"
 
 [dev-dependencies]
+serde_json.workspace = true
 tempfile.workspace = true