audio-voice-recovery

Audio forensics and voice recovery guidelines for CSI-level audio analysis. This skill should be used when recovering voice from low-quality or low-volume audio, enhancing degraded recordings, performing forensic audio analysis, or transcribing difficult audio. Triggers on tasks involving audio enhancement, noise reduction, voice isolation, forensic authentication, or audio transcription.

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リポジトリ: pproenca/dot-skills
ソースの最終更新活動: 2026年5月27日 09:50
検出された SKILL.md の言語: 英語
スター: 194
フォーク: 17

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npx skills add https://github.com/pproenca/dot-skills --skill audio-voice-recovery

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drizzle-nextjs-postgres

Drizzle ORM against PostgreSQL inside a Next.js App Router app. Covers client construction (globalThis singleton across HMR, serverless pool sizing, `prepare:false` behind PgBouncer/Supavisor, driver choice when you need interactive transactions, `server-only`), reads in Server Components under Next.js 16 Cache Components (`use cache` superseding `unstable_cache` and the `revalidate`/`dynamic` segment configs, Suspense boundaries, React `cache()` dedupe), Server Actions (authorization inside the action, `updateTag` vs `revalidateTag`, `after()`), Postgres schema types (timestamptz, identity vs serial, jsonb, numeric-as-string, bigint modes), drizzle-kit migrations (generate vs push, CONCURRENTLY outside the migrator, NOT VALID constraints, rename prompts), transactions and pooled connections, and Postgres query traps (keyset pagination, count cost, driver-dependent `db.execute()` shape, NOT IN nulls, prepared statements). Use when writing or reviewing Drizzle + Postgres code in Next.js.

2026-07-24

relational-data-modeling

Corrects the wrong defaults a model has when designing a relational schema — the DDL decisions an experienced engineer makes differently. Use when creating or reviewing tables, migrations, ER models, or ORM schema definitions. Covers identity and keys (surrogate vs natural, identity vs serial, uuidv7, composite keys that make cross-tenant references impossible), relationships (polymorphic foreign keys the database cannot enforce, referential actions, unindexed FK columns, disjoint subtypes), invariants the engine can prove instead of application code (EXCLUDE, partial unique indexes, CHECK limits, deferrable cycles, NOT VALID), types (timestamptz, exact money, range types, enum vs lookup table), derived and encoded data (generated columns, JSONB as an escape hatch), and time (events vs in-place updates, soft-delete flags that silently disable constraints, temporal keys). NOT for query tuning, index selection for read paths, or connection pooling.

2026-07-23

relational-database-design

Distills a logical relational-database design methodology into rules an agent applies while designing or reviewing a schema. Covers the design sequence (mission → tables → fields → keys → relationships → business rules → views → integrity review), one-subject-per-table decomposition, atomic single-valued fields, candidate/primary/foreign keys, relationship types with deletion rules and participation, the four levels of data integrity, database-vs-application business rules, validation tables, views for derived data, and the flat-file / spreadsheet / RDBMS-driven antipatterns to avoid. The structure is logical and RDBMS-agnostic, and normalized by construction. Use when designing a new relational schema, reviewing or refactoring an existing one, resolving redundant or repeating data, choosing keys, modeling relationships, or deciding where a constraint belongs.

2026-07-23

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name	audio-voice-recovery
description	Audio forensics and voice recovery guidelines for CSI-level audio analysis. This skill should be used when recovering voice from low-quality or low-volume audio, enhancing degraded recordings, performing forensic audio analysis, or transcribing difficult audio. Triggers on tasks involving audio enhancement, noise reduction, voice isolation, forensic authentication, or audio transcription.

Forensic Audio Research Audio Voice Recovery Best Practices

Comprehensive audio forensics and voice recovery guide providing CSI-level capabilities for recovering voice from low-quality, low-volume, or damaged audio recordings. Contains 45 rules across 8 categories, prioritized by impact to guide audio enhancement, forensic analysis, and transcription workflows.

When to Apply

Reference these guidelines when:

Recovering voice from noisy or low-quality recordings
Enhancing audio for transcription or legal evidence
Performing forensic audio authentication
Analyzing recordings for tampering or splices
Building automated audio processing pipelines
Transcribing difficult or degraded speech

Rule Categories by Priority

Priority	Category	Impact	Prefix	Rules
1	Signal Preservation & Analysis	CRITICAL	`signal-`	5
2	Noise Profiling & Estimation	CRITICAL	`noise-`	5
3	Spectral Processing	HIGH	`spectral-`	6
4	Voice Isolation & Enhancement

Tool	Purpose	Install
FFmpeg	Format conversion, filtering	`brew install ffmpeg`
SoX	Noise profiling, effects	`brew install sox`
Whisper	Speech transcription	`pip install openai-whisper`
librosa	Python audio analysis	`pip install librosa`
noisereduce	ML noise reduction	`pip install noisereduce`
Audacity	Visual editing	`brew install audacity`

File	Description
AGENTS.md	Complete compiled guide with all rules
references/_sections.md	Category definitions and ordering
assets/templates/_template.md	Template for new rules
metadata.json	Version and reference information

audio-voice-recovery

インストール方法

ソースファイルを確認

Forensic Audio Research Audio Voice Recovery Best Practices

When to Apply

Rule Categories by Priority

Forensic Audio Research Audio Voice Recovery Best Practices

When to Apply

Rule Categories by Priority

Quick Reference

1. Signal Preservation & Analysis (CRITICAL)

2. Noise Profiling & Estimation (CRITICAL)

3. Spectral Processing (HIGH)

4. Voice Isolation & Enhancement (HIGH)

5. Temporal Processing (MEDIUM-HIGH)

6. Transcription & Recognition (MEDIUM)

7. Forensic Authentication (MEDIUM)

8. Tool Integration & Automation (LOW-MEDIUM)

Essential Tools

Workflow Scripts (Recommended)

Forensic Preflight Workflow (Do This Before Any Changes)

Quick Enhancement Pipeline

How to Use

Reference Files

audio-voice-recovery

ソース情報

インストール方法

ソースファイルを確認

このリポジトリの他の Skills

このリポジトリの他の Skills

Forensic Audio Research Audio Voice Recovery Best Practices

When to Apply

Rule Categories by Priority

Forensic Audio Research Audio Voice Recovery Best Practices

When to Apply

Rule Categories by Priority

Quick Reference

1. Signal Preservation & Analysis (CRITICAL)

2. Noise Profiling & Estimation (CRITICAL)

3. Spectral Processing (HIGH)

4. Voice Isolation & Enhancement (HIGH)

5. Temporal Processing (MEDIUM-HIGH)

6. Transcription & Recognition (MEDIUM)

7. Forensic Authentication (MEDIUM)

8. Tool Integration & Automation (LOW-MEDIUM)

Essential Tools

Workflow Scripts (Recommended)

Forensic Preflight Workflow (Do This Before Any Changes)

Quick Enhancement Pipeline

How to Use

Reference Files