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ClaudeWave

Claude Code Slash Commands · page 7

Slash commands for Claude Code collected from the directory: prompt definitions you can install into ~/.claude/commands with one command.

1,092 slash commands1-command install
  1. Use when a topic needs structured multi-dimensional investigation before planning or decision-making

  2. Generate formal specification package (Product Brief, PRD, Architecture, Epics) through 6-phase document chain

  3. Use when exploring ideas, evaluating approaches, or needing multi-perspective analysis before implementation

  4. Use when a question needs cross-verification from multiple CLI tools or diverse analytical perspectives

  5. Knowledge companion — load context, record companion doc, capture insights, route to skills

  6. Compose reusable workflow templates from natural language

  7. Use when a confirmed plan is ready for implementation

  8. Create or sync milestone worktree for parallel dev

  9. Use when stress-testing a plan, idea, or requirement against codebase reality before brainstorming

  10. Manage editing boundary restrictions

  11. Use when designing, auditing, polishing, or improving frontend UI — websites, dashboards, landing pages, components

  12. Initialize project with auto state detection

  13. Merge milestone worktree branch back to main

  14. Audit current milestone for cross-phase integration gaps

  15. Archive completed milestone and prepare for next

  16. Bump version, generate changelog, tag milestone

  17. Single-command recommendation — pick the best next command from the pool and execute it

  18. Create or edit command overlays from natural language

  19. Use when creating, revising, or verifying an execution plan for a phase or task

  20. Play workflow templates with checkpoint resume

  21. Quick task execution, skip optional agents

  22. Self-running loop controller for adaptive maestro workflow — build, tick, decide in one skill

  23. Execute next pending step in ralph session

  24. Use when the optimal command sequence is unclear and needs automated state-based determination

  25. Generate roadmap with milestone/phase structure from requirements or upstream context

  26. Parallel workflow accelerator — route intent to fixed Workflow scripts for multi-agent concurrent execution

  27. Load and execute tool specs by category or name

  28. Register tool specs - extract, generate, or optimize

  29. Extract design system from code, generate reference package, persist as knowledge assets

  30. Dynamic adversarial workflow generator — scan library, match or generate, execute, persist

  31. Detect version, preview changes, apply workflow upgrades

  32. Auto-route intent to optimal command chain

  33. Rebuild all codebase documentation from scratch

  34. Extract knowledge from artifacts into wiki/spec/issues

  35. Discover issues via multi-perspective analysis

  36. Create, query, update, close, and link issues

  37. Analyze codebase patterns and generate .workflow/kg/extractors.yaml for custom symbol extraction

  38. Capture reusable knowledge as templates, recipes, or tips

  39. Manage knowhow entries (workflow and system)

  40. Audit and prune knowledge across spec / knowhow / artifact stores

  41. Show project dashboard with progress and next steps

  42. Manage wiki graph — health, cleanup, search, stats

  43. Long-running debug cycle — archaeology, diagnosis, fix, confirmation, generalization, discovery, and knowledge persistence

  44. Long-running codebase improvement cycle — multi-dimensional audit, deep diagnosis, targeted fix, verify, generalize, and engineering knowledge persistence

  45. Requirement-driven iterative cycle — plan, execute, strict verify, fix loop until acceptance criteria met

  46. Deep review + fix cycle — archaeology, exploration, multi-dimensional review, targeted fix, generalization, discovery, and knowledge persistence

  47. Long-running UI optimization cycle — visual survey, multi-dimensional audit, divergent exploration, fix, verify, generalize, and design knowledge persistence

  48. Use when test coverage needs automated expansion or existing tests need iterative convergence

  49. Use when bugs, test failures, or unexpected behavior need systematic root cause investigation

  50. Use when accumulated tech debt needs systematic identification and safe reduction

  51. Use after completing a phase to extract lessons, patterns, and improvement opportunities

  52. Use after execution to evaluate code quality across correctness, security, performance, and architecture

  53. Sync codebase docs by tracing git diff impact

  54. Register a domain term into project glossary

  55. Detect and realign .workflow/ artifact drift against code reality after refactoring

  56. gate476

    Run the one-command quality gate and report the real N/N result. Use before claiming any build/review is done.

  57. Scaffold a new design-product project that matches the recommended Claude Code layout (the reference structure). Use when starting a fresh product/app that will be built with this design system.

  58. ship476

    Pre-release gate — run the full gate, responsive + render checks, then produce the release checklist (README badge/current/changelog). Use before tagging a release.

  59. Control thinking token limits via environment variable

  60. Run complete two-agent validation on module+tests (contract extraction + test validation). Binary pass/fail with specific issues.

  61. Full autonomous security workflow — scan, dedup, prep, analyse, consensus, judge, exploit, patch, group

  62. Analyze existing SARIF findings with LLM

  63. Add, list, edit, or remove per-function annotations attached to source files

  64. Audit authentication (JWT, cookies) and security logging coverage automatically

  65. CodeQL deep static analysis with dataflow validation

  66. List all available MANTISHACK commands

  67. Autonomous crash root-cause analysis for C/C++ bugs

  68. CVE patch discovery — find, acquire, and diff the fix commit for a CVE

  69. Generate Mermaid visual maps from /understand or /validate output directories

  70. Generate exploit proof-of-concepts for vulnerabilities (beta)

  71. Binary fuzzing with AFL++ integration

  72. Evidence-backed forensic investigation for GitHub repositories

  73. Generate secure patches for vulnerabilities (beta)

  74. Manage MANTISHACK projects — create, list, status, coverage, findings, diff, merge, report, clean, export

  75. Software Composition Analysis — find vulnerable dependencies, gate CI, fix and pin

  76. Scan a repository with Semgrep and CodeQL

  77. Inspect per-model reliability across decision classes; answer natural-language questions about model competence

  78. Run automated workflow tests for all commands

  79. Map attack surface, trace data flows, hunt vulnerability variants

  80. Validate that vulnerability findings are real, reachable, and exploitable

  81. Web application security scanner (alpha)

  82. One-shot MAXIMAL autonomous pentest — the full scan+validate pipeline PLUS a parallel red-team agent war-game, adversarially verified and stitched into a kill-chain Red Team Report.

  83. Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.

  84. Generate a custom checklist for the current feature based on user requirements.

  85. Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.

  86. Create or update the project constitution from interactive or provided principle inputs, ensuring all dependent templates stay in sync.

  87. Execute the implementation plan by processing and executing all tasks defined in tasks.md

  88. Execute the implementation planning workflow using the plan template to generate design artifacts.

  89. Create or update the feature specification from a natural language feature description.

  90. Generate an actionable, dependency-ordered tasks.md for the feature based on available design artifacts.

  91. Convert existing tasks into actionable, dependency-ordered GitHub issues for the feature based on available design artifacts.

  92. Perform comprehensive data analysis on specified dataset

  93. 自动化完成整个数据分析工作流程,从数据质量检查到最终报告生成

  94. Generate analysis code in specified language and analysis type

  95. Generate research hypotheses and experimental designs based on data patterns

  96. Perform data quality validation, checks, and monitoring for specified dataset

  97. Generate comprehensive analysis reports for specified dataset

  98. Create data visualizations for the specified dataset

  99. Run an accessibility audit on the current project for WCAG compliance.

  100. Reverse-engineer a Product Requirements Document from existing code.