
# sl Audit Skill ## Overview Codebase reconnaissance skill for understanding project structure, tech stack, and module organization. This skill provides patterns for efficient codebase exploration without AI orchestration overhead. **Layer**: L3 (Skill) - Passive context injection **Use when**: You need to understand an unfamiliar codebase or validate architecture assumptions ## When to Load Load this skill when: - First encounter with an unfamiliar codebase - Need to understand project str
# sl-comment Skill **When to Load**: Triggered when AI commands mention "review comments", "comment", or reference `sl comment` CLI. ## Overview The `sl comment` CLI provides review comment management for SpecLedger projects. Comments are stored in Supabase and accessed via the PostgREST API. ## Subcommands | Command | Purpose | Output Mode | |---------|---------|-------------| | `sl comment list [branch-name] [-R owner/repo]` | List all comments (compact) | Truncated previews, reply counts
# sl Dependency Management **When to Load**: Triggered when tasks involve cross-repo specification dependencies, `sl deps` commands, artifact caching, or multi-repo dependency resolution. ## Overview `sl deps` manages external specification dependencies between repositories. Dependencies are declared in `specledger.yaml`, cached locally at `~/.specledger/cache/`, and optionally symlinked into your project's artifacts directory for direct access. ## Subcommands | Command | Purpose | Output M
# sl Issue Tracking ## Overview `sl issue` is the built-in issue tracker for SpecLedger. Use it for multi-session work with complex dependencies; use TodoWrite for simple single-session tasks. ## When to Use sl issue vs TodoWrite ### Use sl issue when: - **Multi-session work** - Tasks spanning multiple compaction cycles or days - **Complex dependencies** - Work with blockers, prerequisites, or hierarchical structure - **Knowledge work** - Strategic documents, research, or tasks with fuzzy bo
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