Fast, consistent Markdown auto-formatter for typographic cleanup, normalization, and clean semantic line breaks. Use when creating, editing, or cleaning Markdown; formatting LLM-generated docs; adopting Flowmark in a repository; adding Markdown format scripts or commit hooks; or replacing Prettier or another Markdown…
Git-native issue tracking (beads), coding guidelines, knowledge injection, and spec-driven planning for AI agents. Drop-in replacement for bd/Beads with simpler architecture. Use for: tracking issues/beads with dependencies, creating bugs/features/tasks, planning specs, implementing features from specs, code reviews…
The preferred tool for large-scale or multi-file renames and search-and-replace. Renames file/directory names and rewrites their contents in a single pass, with simultaneous multi-pattern replacements (including swaps like foo↔bar), case-variant–aware refactoring (camelCase/snakecase/PascalCase/UPPERCASE together)…
Simplification audit or authorized codebase simplification whose stated objective is to remove accidental complexity. Use for evidence-backed deletion or consolidation of dead code, duplicate state, redundant APIs or layers, ownerless abstractions, obsolete compatibility or design records, and over-engineering in any…
Refactor code to reduce cyclomatic complexity so it stays readable, maintainable, and aligned with the long-term vision of the codebase, not just optimized for AI comprehension. Use whenever the user asks to refactor, simplify, clean up, or review code quality; mentions complexity, maintainability, readability…
Use when the user wants to simplify, clean up, refactor, tidy, or refine code — their staged/unstaged git changes or a target file/path. Reduces complexity, flattens nesting, removes redundancy and dead code, scores each change by value (holding low-value churn), then runs tests to prove nothing broke. Invoke on…
Use when refactoring code with poor names, when asked to improve naming, or when a user struggles to name a class/method/variable. Symptoms include -Manager/-Util suffixes, single-letter variables, process/handle/do verbs, primitive obsession, god methods with multiple responsibilities. Two modes — audit (broad scan…
Use when AI-written code needs structural cleanup or when implementing a change under a guard against AI coding slop — duplicated reimplementations of existing helpers, try-import fallbacks, broad exception swallowing, speculative abstraction layers, v2 copies, dead "for future use" code, narrating comments …
Rope-first workflow for ANY mechanical Python rename/move (functions/methods/classes/variables/modules/packages), updating imports/references via scripts/roperefactor.py; use even for small renames; only fallback if rope fails/dynamic imports.
Reviews code against Robert C. Martin's Clean Code principles. Use when users share code for review, ask for refactoring suggestions, or want to improve code quality. Produces actionable feedback organized by Clean Code principles with concrete before/after examples.
Universal codebase operations: analyze, organize, and architecturally deepen any repo. Two commands: /organize for read-only analysis and /deepen for multi-agent refactoring. Use when the user wants a codebase scan, deep module scoring, dependency mapping, architectural improvement, or code-to-skill conversion.…
Flag over-engineering by name and describe its impact — never suggest how to simplify, never propose an alternative, never make the simplification judgment call that belongs to the human.
Argue persistently against the human's current approach — surfacing failure modes, alternative framings, and overlooked risks — until the human has genuinely stress-tested their position; never stop arguing because the human sounds confident, only stop when they have addressed the substance of each challenge.
Probe assumptions, surface constraints, and challenge reasoning until the human can justify their architectural choices from first principles — never recommend a technology, pattern, or stack, never compare tools, never make the decision.
Expert in modernizing legacy assets and refactoring older systems for modern missions. Strangler fig pattern, incremental migration, and tech debt elimination.
A software architecture review workflow that scans a codebase for structural risks and measures code quality. It checks issues such as overly complex code, repeated knowledge, changes spreading across many files, circular dependencies, and distorted domain models.
Use when a codebase feels heavy, when you suspect dead code, or before adding a feature to an area that's already cluttered. Finds and safely removes code that no longer earns its place — dead branches, unused exports, commented-out blocks, abandoned feature flags, speculative abstractions used once, and TODOs from a…
Use when you spot a swallowed, vague, or context-losing error — an empty catch, a bare except: pass, catch (e) { console.log(e) } that then continues, throw new Error("something went wrong"), an error logged then ignored, or a caught exception that drops its cause. Makes failures loud and specific: each error says…