irfad7

When the user needs to perform the same operation across multiple files, components, or entities. Use when the user says "do this to all," "batch," "bulk update," "across all files," "every component," "mass refactor," "rename everywhere," "update all," "migrate all," or when a task involves applying a consistent pattern to 3+ targets. Orchestrates parallel processing of repetitive tasks with cons

When the user wants a thorough code review of changes, a PR, a file, or a feature branch. Use when the user says "review this," "code review," "check my code," "what's wrong with this," "review my PR," "look over this," "critique this," "review before merge," or when submitting code for quality assessment. Performs multi-pass review covering correctness, security, performance, maintainability, and

When you or the user are going in circles, stuck on a problem, or repeating failed approaches. Use when the user says "I'm stuck," "this isn't working," "we keep going in circles," "try something different," "nothing works," "help," or when you detect that you've attempted the same category of solution 2+ times without success. Forces a structured step-back, reframe, and fresh approach.

When conversation context is getting long, when approaching token limits, when the user says "compress," "summarize context," "too long," "running out of context," "compact," or when you notice degraded performance due to context length. Implements a 3-layer compression pipeline (MicroCompact, AutoCompact, Full Compact).

When ending a work session and wanting to capture what was accomplished, what was learned, and what to do next. Use when the user says "session review," "what did we do," "wrap up," "summarize session," "weekly review," "retrospective," "what happened today," "debrief," or at natural session endings. Reviews the session transcript, extracts learnings, identifies patterns, and produces an actionabl

When the user wants to find bugs, test edge cases, stress-test code, or perform adversarial analysis of their codebase. Use when the user says "find bugs," "break this," "what could go wrong," "red team," "hunt bugs," "adversarial test," "edge cases," "stress test," "what did I miss," "pen test this logic," or before any major release. Operates with red team psychology — assumes everything is brok

When ending a session, consolidating memory, or when memory files feel stale or contradictory. Use when the user says "dream," "consolidate memory," "clean up memory," "merge notes," "memory maintenance," "what do you remember," "update your knowledge," "session end," or when memory/context files have accumulated noise over multiple sessions. Performs cross-session memory synthesis inspired by KAI

When contributing to public or open-source repositories where AI attribution should be hidden. Use when the user says "stealth mode," "undercover," "no AI attribution," "hide AI," "contribute anonymously," "clean commits," "no co-authored-by," or when working on repos where AI involvement should not be visible. Strips all AI fingerprints from commits, PRs, code comments, and generated content.

When the user wants to review past decisions, understand why something was built a certain way, audit decision quality, or learn from past reasoning. Use when the user says "why did we," "look back," "thinkback," "decision review," "was that the right call," "what were we thinking," "review our decisions," "decision audit," "trace back," "replay thinking," or when revisiting old code and needing t

When the user needs accurate effort estimates for tasks, features, or projects. Use when the user says "how long will this take," "effort estimate," "estimate this," "scope this," "size this," "time estimate," "sprint planning," or when planning work. Unlike generic estimates, this skill calibrates against YOUR actual velocity — past estimates vs actuals — so estimates get more accurate over time.

When the user wants to generate documentation from their codebase. Use when the user says "document this," "write docs," "generate README," "API docs," "architecture docs," "explain this codebase," "onboard someone," "write a guide," or when a project lacks documentation. Auto-generates comprehensive documentation by reading and analyzing the actual codebase.

When working on sensitive projects, proprietary code, or systems where context leakage is a concern. Use when the user says "protect this," "sensitive project," "don't leak," "sanitize output," "clean context," "proprietary," "confidential," or when working across multiple projects where context bleed between them could be problematic. Implements defensive patterns to prevent sensitive context fro