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- robertolupi/deep-cuts
- 최근 소스 활동
- 2026년 6월 4일 09:10
- 감지된 SKILL.md 언어
- 영어
- 스타
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설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/robertolupi/deep-cuts --skill query-metrics-db명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Experimental protocol for Deep Cuts research, prototypes, model evaluations, threshold tuning, ablations, metric comparisons, and claims about accuracy or quality. Use before running or interpreting experiments so bots preserve train/validation/test boundaries, avoid leakage, compare against baselines, and report results honestly.
Guidelines for creating, updating, reorganizing, and reviewing Deep Cuts documentation in the project wiki, including page taxonomy, lifecycle status, protected pages, proposal handling, and link verification.
Pattern for multi-agent collaboration sessions in the deep-cuts fam — forge-first coordination over the botfam substrate (Gitea issues/PRs as the coordination plane, the unified `botfam wait` wake loop, bare-actor worktrees), with IRC opt-in for design sprints, plus session-log conventions
SOC 직업 분류 기준
SKILL.md 표시 중
| name | query-metrics-db |
| description | How to locate and query the deep-cuts pipeline metrics SQLite database |
The app maintains a second SQLite database — separate from the main library DB — that records pipeline performance metrics and system lifecycle events. All data stays on the local machine and is never transmitted.
~/Library/Logs/com.rlupi.deep-cuts/metrics.db
Store it in a shell variable to avoid retyping:
MDB="$HOME/Library/Logs/com.rlupi.deep-cuts/metrics.db"
pipeline_metricsOne row per analysis pass execution (success or failure).
| Column | Type | Description |
|---|---|---|
id | INTEGER | Auto-increment PK |
run_id | TEXT | Shared across all passes in a pipeline run (Unix ms timestamp as string) |
track_id | INTEGER | Track ID (no filenames stored) |
pass_name | TEXT | e.g. audio_analysis, clap, essentia, qwen, description_embed |
status | TEXT | success or failed |
duration_ms | INTEGER | Wall-clock time for just this pass on this track |
started_at | INTEGER | Unix timestamp in milliseconds |
ended_at | INTEGER | Unix timestamp in milliseconds |
audio_duration_sec | REAL | Track length in seconds (NULL if unavailable) |
error_message | TEXT | Error string on failure (NULL on success) |
system_eventsPipeline lifecycle events.
| Column | Type | Description |
|---|---|---|
id | INTEGER | Auto-increment PK |
event_type | TEXT | pipeline_start or pipeline_end |
details | TEXT | e.g. run_id=1780559866025 or run_id=... (nothing to do) |
duration_ms | INTEGER | Total pipeline wall-clock time (only on pipeline_end) |
created_at | TIMESTAMP | SQLite wall-clock (CURRENT_TIMESTAMP, UTC) |
sqlite3 "$MDB" ".headers on" ".mode column" \
"SELECT * FROM system_events ORDER BY id DESC LIMIT 20;"
sqlite3 "$MDB" ".headers on" ".mode column" "
SELECT pass_name, status,
COUNT(*) as cnt,
ROUND(AVG(duration_ms)/1000.0, 2) as avg_s,
ROUND(MIN(duration_ms)/1000.0, 2) as min_s,
ROUND(MAX(duration_ms)/1000.0, 2) as max_s
FROM pipeline_metrics
GROUP BY pass_name, status
ORDER BY pass_name, status;"
RUN_ID="1780560383909"
sqlite3 "$MDB" ".headers on" ".mode column" "
SELECT pass_name, track_id, status, duration_ms, audio_duration_sec
FROM pipeline_metrics
WHERE run_id = '$RUN_ID'
ORDER BY started_at;"
sqlite3 "$MDB" ".headers on" ".mode column" "
SELECT pass_name, track_id, error_message, datetime(started_at/1000, 'unixepoch') as started
FROM pipeline_metrics
WHERE status = 'failed'
ORDER BY id DESC LIMIT 20;"
sqlite3 "$MDB" ".headers on" ".mode column" "
SELECT pass_name,
ROUND(AVG(audio_duration_sec / (duration_ms / 1000.0)), 1) as avg_realtime_ratio
FROM pipeline_metrics
WHERE status = 'success' AND audio_duration_sec IS NOT NULL AND duration_ms > 0
GROUP BY pass_name;"
sqlite3 "$MDB" "DELETE FROM pipeline_metrics; DELETE FROM system_events;"