A suite of AI coding agent skills that build and maintain a shadow knowledge base for any codebase.
About the project
ShadowFrog is a suite of coding-agent skills that maintains a file-backed knowledge base of tacit information about a codebase, such as fragile dependencies, untested invariants, and hard-to-notice edge cases. It helps coding agents preserve lessons from code reading, experiments, and conversations across future work. The catalogue contains skills that create, update, explore, organize, and view this shadow knowledge base.
Run autonomous experimentation while the user is AFK. Uses 6 investigation categories (investigation, bug hunting, feature design, refactoring, optimization, security audit) to systematically discover non-obvious behaviors. Every task is an experiment — implement in worktrees, commit to persistent dream branches, and…
Initialize a shadow knowledge base for any codebase. Creates a .shadow/ directory that mirrors the source tree with markdown files for AI-discovered insights. Run this once per repo before using other shadow-frog skills. Refuses to overwrite an existing .shadow/ unless --reset is passed.
Clean and consolidate the shadow knowledge base. Scans all shadow files for duplicate discoveries (same claim, different wording), near-duplicates (one extends another), and conflicting entries (contradicting claims). Merges duplicates, resolves conflicts by investigating the code, and asks the user only when…
Update the shadow knowledge base after code changes and from conversational insights. Detects what changed via git diff, refreshes per-file shadows, captures knowledge shared by the user during the session, and updates cross-cutting discoveries. Invoke manually with /shadow-frog-update; the preToolUse hook will remind…
Help users browse and visualize the shadow knowledge base: overview, search for files or symbols or text, view preferences, or see recent discoveries. Invoke when the user wants to see what's in the shadow, get an overview, or find specific knowledge.
Use a shadow knowledge base to understand any codebase. The .shadow/ directory mirrors the source tree with markdown files containing behavioral insights — known bugs, edge cases, implicit contracts, and user preferences. Always check the shadow before editing, debugging, or investigating code. When the user shares…
Generate grounded software feature-task briefs with a small, bounded ideation budget instead of implementing every idea. Read focused source and optional shadow/dream evidence, grow or resume a persistent proposal tree, and obtain independent shortlist judgments. Run only decision-changing probes of existing behavior.…
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+1 6d agoA106 tokens
originalMIT
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: