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Claude Skills by naimkatiman
github.com/naimkatiman62 skills0 installs52 views
- continuous-improvementInstall structured self-improvement loops with instinct-based learning into Claude Code — research, plan, execute, verify, reflect, learn, iterate. On-demand or weekly analysis to save tokens. Supports multi-agent parallel analysis.Votes: 0GitHub stars: 7
- PlansAdd a Tier-2 companion skill named `wild-risa-balance` that gives the agent a deliberate switch between two opposing decision modes:Votes: 0GitHub stars: 7
- Deploy ReceiptEnforces Law 4 (Verify Before Reporting) of the 7 Laws of AI Agent Discipline at the deploy seam. A merge into a branch that auto-deploys is not "done" until the deploy provider reports the merged commit SHA running and a healthcheck endpoint returns 200. Companion to the vendored `finishing-a-development-branch` skill — does not replace it, runs after it for projects on Railway, Cloudflare Workers, Vercel, Netlify, Fly.io, or any other auto-deploy target.Votes: 0GitHub stars: 7
- GateguardEnforces Law 1 (Research Before Executing) of the 7 Laws of AI Agent Discipline. Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents.Votes: 0GitHub stars: 7
- Grill MeEnforces Law 1 (Research Before Executing) of the 7 Laws of AI Agent Discipline. Interview the user relentlessly about a plan or design until shared understanding is reached, resolving every branch of the decision tree before any code is written. Ported from mattpocock/skills under MIT.Votes: 0GitHub stars: 7
- Grill With DocsEnforces Law 1 (Research Before Executing) and Law 7 (Learn From Every Session) of the 7 Laws of AI Agent Discipline. Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates CONTEXT.md + ADRs inline as decisions crystallise. Ported from mattpocock/skills under MIT.Votes: 0GitHub stars: 7
- HandoffEnforces Law 5 (Reflect After Every Session) of the 7 Laws of AI Agent Discipline. Compact the current conversation into a handoff document for another agent to pick up. Ported from mattpocock/skills under MIT.Votes: 0GitHub stars: 7
- Proceed With The RecommendationOrchestrator for all 7 Laws of AI Agent Discipline. Walks an agent-emitted recommendation list top-to-bottom under the 7 Laws — restate, route per item, verify before advancing, reflect at the end, close with the mandatory three-section block. Standalone with inline fallbacks; trigger phrases are matched by the companion hook, not enumerated here.Votes: 0GitHub stars: 7
- RalphEnforces Law 6 (Iterate Means One Thing) of the 7 Laws of AI Agent Discipline at PRD scale. Ralph is an autonomous AI agent loop that runs repeatedly until all PRD items are complete. Converts PRDs to executable JSON, implements stories iteratively with quality checks, and tracks progress.Votes: 0GitHub stars: 7
- Recovery ClassificationEnforces Law 4 (Verify Before Reporting) of the 7 Laws of AI Agent Discipline. After any failure in the verification ladder or auto-loop, classify the failure class before retrying — provider, tool-schema, deterministic-policy, git, worktree, runtime — so retry-vs-pause-vs-self-heal-vs-stop is an intentional decision, not a generic 'try again'.Votes: 0GitHub stars: 7
- State ReconciliationEnforces Law 4 (Verify Before Reporting) of the 7 Laws of AI Agent Discipline. Pre-dispatch invariant: reconcile DB-vs-disk-vs-memory state before any unit runs, so a stale flag, missing artifact, or out-of-sync row never re-dispatches a unit that already completed or never started.Votes: 0GitHub stars: 7
- Strategic CompactEnforces Law 5 (Reflect After Every Session) of the 7 Laws of AI Agent Discipline at phase boundaries. Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.Votes: 0GitHub stars: 7
- SuperpowersLaw activator for the 7 Laws of AI Agent Discipline. Unified four-source dispatcher — routes tasks to the correct Law-aligned specialist across the CI plugin (tdd-workflow, verification-loop, gateguard, ralph, deploy-receipt) and four registered upstream companions (Obra superpowers, addy agent-skills, ruflo-swarm, oh-my-claudecode) so the right discipline fires automatically instead of the agent skipping a step. Product-management coverage comes from phuryn/pm-skills via an out-of-band marke...Votes: 0GitHub stars: 7
- Tdd WorkflowEnforces Law 3 (One Thing at a Time) and Law 4 (Verify Before Reporting) of the 7 Laws of AI Agent Discipline. Use this skill when writing new features, fixing bugs, or refactoring code. Enforces test-driven development with 80%+ coverage including unit, integration, and E2E tests.Votes: 0GitHub stars: 7
- Token Budget AdvisorEnforces Law 2 (Plan Is Sacred) of the 7 Laws of AI Agent Discipline by making token-budget tradeoffs explicit before the response is composed. Offers the user an informed choice about how much response depth to consume before answering. Use this skill when the user explicitly wants to control response length, depth, or token budget. TRIGGER when: "token budget", "token count", "token usage", "token limit", "response length", "answer depth", "short version", "brief answer", "detailed answer",...Votes: 0GitHub stars: 7
- Verification LoopEnforces Law 4 (Verify Before Reporting) of the 7 Laws of AI Agent Discipline. A comprehensive verification system for agent coding sessions covering build, types, lint, tests, security, and diff with a PASS/FAIL report.Votes: 0GitHub stars: 7
- Wild Risa BalanceEnforces Law 2 (Plan Is Sacred) of the 7 Laws of AI Agent Discipline. Decision-framing lens that pairs WILD generation with RISA execution when emitting recommendation lists. Not a runtime hook.Votes: 0GitHub stars: 7
- Workspace Surface AuditEnforces Law 1 (Research Before Executing) of the 7 Laws of AI Agent Discipline. Audits the active repo, MCP servers, plugins, connectors, env surfaces, and harness setup, then recommends the highest-value continuous-improvement-native skills, hooks, agents, and operator workflows. Use when the user wants help setting up Claude Code or understanding what capabilities are actually available in their environment.Votes: 0GitHub stars: 7
- Worktree SafetyEnforces Law 4 (Verify Before Reporting) of the 7 Laws of AI Agent Discipline. Pre-dispatch invariant: validate worktree root before any source-writing tool call. Catches missing .git, fallback path-only creation, stale leases, foreign-session ownership, and non-worktree git operations before they corrupt history.Votes: 0GitHub stars: 7
- Ai Slop CleanerClean AI-generated code slop with a regression-safe, deletion-first workflow and optional reviewer-only modeVotes: 0GitHub stars: 7
- AskProcess-first advisor routing for Claude, Codex, Gemini, Antigravity, Grok, or Cursor via `omc ask`, with artifact capture and no raw CLI assemblyVotes: 0GitHub stars: 7
- AutopilotFull autonomous execution from idea to working codeVotes: 0GitHub stars: 7
- AutoresearchStateful single-mission improvement loop with strict evaluator contract, markdown decision logs, and max-runtime stop behaviorVotes: 0GitHub stars: 7
- CancelCancel any active OMC mode (autopilot, ralph, ultragoal, swarm, ultrapilot, pipeline, team) and clean up retired legacy stateVotes: 0GitHub stars: 7
- Configure NotificationsConfigure notification integrations (Telegram, Discord, Slack) via natural languageVotes: 0GitHub stars: 7
- DebugDiagnose the current OMC session or repo state using logs, traces, state, and focused reproductionVotes: 0GitHub stars: 7
- Deep InterviewSocratic deep interview with mathematical ambiguity gating before explicit execution approvalVotes: 0GitHub stars: 7
- DeepinitDeep codebase initialization with hierarchical AGENTS.md documentationVotes: 0GitHub stars: 7
- External ContextInvoke parallel document-specialist agents for external web searches and documentation lookupVotes: 0GitHub stars: 7
- HudConfigure HUD display options (layout, presets, display elements)Votes: 0GitHub stars: 7
- Omc DoctorDiagnose and fix oh-my-claudecode installation issuesVotes: 0GitHub stars: 7
- Omc SetupInstall or refresh oh-my-claudecode for plugin, npm, and local-dev setups from the canonical setup flowVotes: 0GitHub stars: 7
- PlanStrategic planning with optional interview workflowVotes: 0GitHub stars: 7
- Project Session ManagerWorktree-first dev environment manager for issues, PRs, and features with optional tmux sessionsVotes: 0GitHub stars: 7
- RalplanConsensus planning entrypoint that auto-gates vague ralph/autopilot/team requests before executionVotes: 0GitHub stars: 7
- ReleaseGeneric release assistant — analyzes repo release rules, caches them in .omc/RELEASE_RULE.md, then guides the releaseVotes: 0GitHub stars: 7
- Self ImproveAutonomous evolutionary code improvement engine with tournament selectionVotes: 0GitHub stars: 7
- SkillManage local skills - list, add, remove, search, edit, setup wizardVotes: 0GitHub stars: 7
- SkillifyTurn a repeatable workflow from the current session into a reusable OMC skill draftVotes: 0GitHub stars: 7
- TeamN coordinated agents on shared task list using Claude Code implicit agent teamsVotes: 0GitHub stars: 7
- TraceEvidence-driven tracing lane that orchestrates competing tracer hypotheses in Claude built-in team modeVotes: 0GitHub stars: 7
- Visual VerdictStructured visual QA verdict for screenshot-to-reference comparisonsVotes: 0GitHub stars: 7
- WikiLLM Wiki — persistent markdown knowledge base that compounds across sessions (Karpathy model)Votes: 0GitHub stars: 7
- Monitor StreamStream live swarm events using the Monitor tool for real-time observabilityVotes: 0GitHub stars: 7
- Swarm InitInitialize a multi-agent swarm with anti-drift configurationVotes: 0GitHub stars: 7
- PlansDate: 2026-06-10 Branch: `feat/model-forward-skill` Status: complete (verified 2026-06-10)Votes: 0GitHub stars: 7
- AuditEnforces Law 4 (Verify Before Reporting) of the 7 Laws of AI Agent Discipline. Audits a window of recent commits for real defects, confirms each finding before touching code so false positives die first, and checks every surface a change touches — so 'looks done' is never mistaken for 'is correct'.Votes: 0GitHub stars: 7
- Goal MonitorEnforces Law 2 (Plan Is Sacred) of the 7 Laws of AI Agent Discipline. Detects when a session has drifted away from its stated goal by scoring recent tool activity against the '## Goal' section of task_plan.md, so drift is caught mid-session instead of at end-of-session reflection.Votes: 0GitHub stars: 7
- Intent Driven DevelopmentEnforces Law 2 (Plan Is Sacred) of the 7 Laws of AI Agent Discipline. Turn an ambiguous or high-impact change into scoped, verifiable acceptance criteria (observable AC-NNN, explicit in/out scope, named verification methods, and a [revised] protocol that forbids silently dropping a criterion) before or alongside implementation, so the plan that gets built is the plan that was agreed, not an invented default. Use when clarifying a feature, defining acceptance criteria, de-risking a security/da...Votes: 0GitHub stars: 7
- Model ForwardEnforces all 7 Laws as a standing stance — go with Claude Code and the model, not against it. Skills are scaffolding that merges into the model over time; the durable core is goal-driven execution (the higher the stated goal, the better) plus self-discipline guardrails.Votes: 0GitHub stars: 7