alirezarezvani

by Alireza Rezvani

WCAG 2.2 accessibility audit and fix skill for React, Next.js, Vue, Angular, Svelte, and HTML. Static scanner detecting 20+ violation types, contrast checker with suggest mode, framework-specific fix patterns, CI-friendly exit codes.

by Alireza Rezvani

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO (which optimizes for search rankings), AEO optimizes for citation in LLM-generated responses. Ships 3 stdlib Python tools (aeo_audit.py for E-E-A-T + structure scoring, aeo_optimizer.py for content rewriting in conservative/balanced/aggressive modes, citation_tracker.py for local-first citation ledger), 3 references citing 7+ authoritative sources each (E-E-A-T methodology, per-LLM citation patterns, AEO-vs-SEO strategy), and industry-aware thresholds for 8 industries (saas/healthcare/finance/legal/ecommerce/b2b/media/education) with stricter YMYL calibration. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'E-E-A-T audit', 'LLM citation strategy', 'answer engine optimization'.

by Alireza Rezvani

Turn any domain folder of skills into a bounded agentic loop: a manifest builder inventories a domain's skills/tools/checks, a goal compiler turns a goal into a verifiable task plan (refusing vague goals with forcing questions), and a JSON-backed loop controller drives execute->verify->close with retry caps, controller-run verification (no verification theater), human escalation on exhausted budgets, and a close gate that refuses while any task is unverified. Ships 3 stdlib Python tools, 18 committed per-domain harness manifests + JSON schema, 3 references citing the 2024-2026 agent-harness canon, harness-runner agent + /cs:harness command. Use when an agent should pick up a goal and drive it to a verified close across a domain.

by Alireza Rezvani

Turn Anthropic's launch-your-agent reference skill into a full domain plugin for building Claude Managed Agents (CMA). Every session starts with a goal (./my-agent/goal.json, surfaced by an opt-in AGENT_LAUNCHER_SESSION=1 SessionStart hook and driven by /cs:goal); a deterministic loop_compiler.py compiles that goal into a grade->iterate loop (CMA user.define_outcome self-grading, bounded by max_iterations), a recurring cron scheduled-deployment loop (run without you), or a single-pass interview->stage->launch workflow. 6 skills: agent-launcher-orchestrator (context: fork goal router) + interview (build sheet: primitives table + v1/v2 deferrals + eval plan) + stage-launch (validated env/agent/session/kickoff payloads + resumable BYOK curl launch script that never prints the key) + grade-iterate (outcome/rubric + verdict reader + held-back eval scaffold) + run-without-you (POSIX-cron deployment + NEXT-DIRECTIONS) + wrap-up (primitive inventory + regenerated overview HTML + next upgrades). 18 stdlib-only deterministic scaffolder tools (no network/API calls; live launches emitted as BYOK curl), 4 agents (orchestrator + interviewer + grader + deployer), 8 commands, opt-in SessionStart/SessionEnd hooks, 5 shared references, 4 assets. Validators enforce CMA limits (<=20 skills/session, <=8 memory stores, <=20 roster / 25 threads / depth-1 multiagent, max_iterations 1..20, <=20 creds/vault, <=1000 deployments/org). Inspired by anthropics/launch-your-agent (Apache-2.0); independent re-implementation, not a fork.

by Alireza Rezvani

A four-tier memory ladder for Claude Code where promotion is earned by recurrence, not asserted by confidence. L0 raw transcripts are never injected; L1 candidate atoms are gitignored and recalled on lexical relevance per prompt; L2 project context loads once per session; L3 stable persona is always loaded. Promotion from L1 to L2 requires at least three distinct sessions spanning at least two distinct calendar days (a stated claim needs two sessions, still spread across days; a deterministically verified claim is the only single-observation path), and L2 to L3 requires two distinct projects and thirty days. Two gates refuse rather than guess: a claim whose text was altered by the seventeen-pattern redaction pass never promotes on evidence alone, and a claim with an open contradiction freezes until a human resolves it, found by reverse join because the newer atom carries no flag. Three hooks run the loop unattended and every one fails open. Nothing reaches a committed CLAUDE.md without an explicit human adopt that backs both files up first. Ships five stdlib scripts, three hooks, a cs-memory-curator agent, a /cs:memory command, a JSON schema, a sixty-nine-check example validator, and a design document with its open decisions ranked by what they gate.

by Alireza Rezvani

Multi-agent collaboration plugin for Claude Code. Spawn N parallel subagents that compete on code optimization, content drafts, research approaches, or any problem that benefits from diverse solutions. Evaluate by metric or LLM judge, merge the winner. 7 slash commands, agent templates, git DAG orchestration, message board coordination.

by Alireza Rezvani

Agile product ownership for backlog management and sprint execution. User story generation (INVEST-compliant), acceptance criteria patterns (Given/When/Then, rule-based, checklist), epic breakdown with 5 split techniques, sprint planning with velocity-based capacity math, and weighted backlog prioritization. Includes user_story_generator Python tool.

by Alireza Rezvani

Marc Andreessen-mode decision and productivity skill. A blunt, market-first operator that pressure-tests ventures, ideas, features, and career bets through Andreessen's documented frameworks (market > team > product; product/market fit is the only milestone that matters; bias to build) and runs his 3x5-card + Anti-Todo daily routine. Runs on a fixed anti-sycophancy operating prompt: leads with the strongest counterargument, never validates premises, no disclaimers, explicit confidence levels, never apologizes for disagreeing. Issues hard verdicts (BUILD-POUR-FUEL / MARKET-FIRST-DERISK / KILL-OR-REPICK-MARKET) backed by deterministic stdlib tools.

by Alireza Rezvani

Master Apple's Human Interface Guidelines (HIG) with focus on 2026 Liquid Glass aesthetics. Design and audit iOS, macOS, and visionOS apps for full compliance and premium feel. Includes hig_checker Python tool for tap targets, contrast, and accessibility validation. Reference docs cover visual design, platform specifics (iOS/macOS/visionOS), and accessibility best practices.

by leoal

Company Architect: builds a business from scratch as an OKF (Open Knowledge Format) bundle — a tree of version-controllable .md files with frontmatter type, links forming a graph, and reserved index.md/log.md, readable by humans and agents. Guides the founder through a 12-phase interview (foundation, strategy, market, financial, sales, marketing, product, operations, tech, people, legal, governance), one phase at a time, and generates conformant markdown concepts. 3 stdlib tools: scaffold_bundle (bundle scaffolding), okf_linter (validates type/reserved files/links), index_generator (regenerates the index.md files). Standalone-installable; also bundled in c-level-skills.

by Alireza Rezvani

Autonomous experiment loop that optimizes any file by a measurable metric. 5 slash commands, 8 evaluators, configurable loop intervals (10min to monthly).

by Alireza Rezvani

Self-Mirror consciousness loop for human-like AI responses. Adds inner dialogue (Self → Mirror → Conscious Response) to make AI output feel authentic, not robotic. Zero dependencies — pure prompt technique.

by Alireza Rezvani

Converts books, documentation folders, and source collections (PDF, EPUB, DOCX, HTML, Markdown, RST, AsciiDoc, RTF, MOBI/AZW) into structured agent skills: a master SKILL.md with core frameworks and a topic index, on-demand chapter files, a glossary, a patterns file, and a decision cheatsheet. Ships 4 stdlib-only tools (multi-format extractor with invisible-Unicode sanitization, four-family generated-skill validator, pre/post-flight token budget estimator, and a plugin emitter that wraps a compiled skill as an installable claude-skills package), 5 references citing 7-8 sources each (including the full step-by-step conversion workflow), a cs-book-to-skill agent, and /cs:book-to-skill + /cs:book-to-plugin commands. Use when the user wants to study a document with an agent, apply an author's frameworks while working, turn internal docs or standards into a reusable knowledge base, or package a compiled book skill as a plugin.

by Alireza Rezvani

4 business & growth skills plus a router: customer success manager (health scoring, churn), sales engineer (RFP analysis, PoC planning), revenue operations (pipeline, forecast accuracy, GTM), and contract & proposal writer. Agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw.

by Alireza Rezvani

Business investment analysis and capital allocation advisor. Use when evaluating whether to invest in equipment, real estate, a new business, hiring, technology, or any capital expenditure. Also use f

by Alireza Rezvani

6 BizOps skills + 1 orchestrator: process-mapper (BPMN + bottleneck + cycle-time), vendor-management (SLA + risk + scorecard), capacity-planner (Erlang-C queueing math for ops teams), internal-comms (ADKAR + Kotter 8-step change comms), knowledge-ops (SOP + runbook authoring with 5W2H validation, context: fork), procurement-optimizer (UNSPSC-aligned spend categorization + supplier consolidation). Orchestrator skill uses context: fork to route inquiries to the right sub-skill via Matt Pocock grill discipline. 18 stdlib-only Python tools, 24+ reference docs each citing ≥7 authoritative sources, asset templates per skill. Distinct from business-growth (external sales) and c-level-advisor (strategic).

by Alireza Rezvani

Founder-mode executive team plugin: 13 cs-* C-suite agents (CFO, CMO, CRO, CPO, COO, CHRO, CISO, Chief of Staff, General Counsel, Chief Data Officer, Chief AI Officer, Chief Customer Officer, VP of Engineering) plus 21 /cs:* slash commands for forcing-question office hours (incl. /cs:vpe-review), multi-role boardroom deliberation, strategic sprint pipeline, and meta routing. Wraps the 33 c-level skills (including vpe-advisor with delivery throughput DORA analyzer + eng hiring funnel calculator + eng team structure designer) with cognitive gearing and artifact handoffs.

by Alireza Rezvani

33 C-level advisory skills (persona layer: install the separate companion c-level-agents plugin for 13 cs-* persona agents + 21 /cs:* slash commands). Complete virtual board of directors with CEO, CTO, COO, CPO, CMO, CFO, CRO, CISO, CHRO advisors plus General Counsel, Chief Data Officer, Chief AI Officer, Chief Customer Officer, and VP of Engineering (delivery throughput DORA analyzer, eng hiring funnel calculator, eng team structure designer), executive mentor, founder coach, Chief of Staff router, board meetings, decision logger, board deck builder, scenario war room, competitive intel, org health diagnostic, M&A playbook, international expansion, culture architect, change management, strategic alignment, and the founder-mode plugin (office-hours, boardroom, brief/decide/execute/post-mortem pipeline, cross-model consensus, decision freeze).

by Alireza Rezvani

Brain-dump organizer. Ingests an unstructured stream of mixed thoughts, tasks, ideas and transforms it into a clean four-section actionable system (Projects/Ideas, Tasks, Connections, How I Can Help) with zero information loss. Fast-to-action by design — no upfront intake. Asks at most one mid-organization clarifying question when a single item is genuinely ambiguous between task and project. Workspace detection is real (Glob/Grep) — never fabricates connections. Source spec: megaprompts/05-capture-megaprompt.md (PR #657).

by Alireza Rezvani

Ultra-compressed communication mode. Cuts token usage ~75% by dropping filler, articles, and pleasantries while keeping full technical accuracy. Enhanced from Matt Pocock's MIT-licensed caveman skill (https://github.com/mattpocock/skills) with: (1) stdlib Python tools (text compressor, token-savings estimator, caveman-style linter), (2) 3 reference docs citing 5+ authoritative sources each (compression principles, technical communication patterns, when caveman backfires), (3) cs-caveman-mode persona agent + /cs:caveman slash command. Matt's voice and persistence rules preserved verbatim per MIT. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman.

by Alireza Rezvani

End-to-end chaos engineering discipline: design experiments with hypothesis + steady-state metric + blast radius + abort criteria, calculate risk score against error budget, and generate blameless postmortems. 3 stdlib Python tools (experiment_designer, blast_radius_calculator, experiment_postmortem), 4 references on chaos principles + experiment design + 7-attack taxonomy + tooling landscape (Chaos Toolkit/Mesh/Litmus/Gremlin/AWS FIS/DIY), templates for plans + postmortems, and a /chaos-experiment slash command. Composes with feature-flags-architect (kill switches as abort triggers) and kubernetes-operator (chaos targets).

by Alireza Rezvani

Chief AI Officer advisory: model build-vs-buy calculator (API vs fine-tune vs build with 3-year TCO across 6 paths + breakeven balancing economics with practical feasibility), AI risk classifier (EU AI Act tier with 7 Article citations + US state patchwork: NYC LL 144, CO AI Act, IL HB 53, CA SB 1001, IL BIPA + industry overlays for FDA AI/ML, CFPB Circular 2023-03, NYDFS Reg 23, NAIC, ECOA, Fed SR 11-7), AI cost economics (API vs self-hosted breakeven with 2026 pricing across A100/H100, utilization reality, hidden costs). 4 in-depth references each citing 5+ authoritative sources. Stdlib-only. Standalone-installable; also bundled in c-level-skills. Strategic only - does not duplicate engineering AI/ML skills.

by Alireza Rezvani

Chief Customer Officer advisory for startups: retention decomposition analyzer (honest GRR vs NRR + 7-category churn taxonomy), customer segmentation designer (4-tier framework + ICP fit scoring + kill list), CS coverage calculator (pooled vs named CSM models + ratio math + 12-month hiring plan). 4 in-depth references: retention decomposition, customer segmentation strategy, CS coverage model, CS team org evolution (CSM vs Support vs AM vs IM vs CS Ops). Stdlib-only. Standalone-installable; also bundled in c-level-skills. Strategic only - does not duplicate business-growth tactical CS skills.

by Alireza Rezvani

Chief Data Officer advisory: AI training data audit (origin x class x use-case matrix with GDPR Art. 6 + EU AI Act citations -> GO/MITIGATE/NO-GO per source), data product strategy picker (warehouse vs lakehouse vs mesh + 6-layer build-vs-buy + 12-month sequencing), data asset valuator (strategic value 0-10 + M&A multiplier with carve-out penalties + 3 ranked productization paths). 4 references answering one decision each: training rights, data product strategy, customer-data-as-asset, data team org evolution. Stdlib-only. Standalone-installable; also bundled in c-level-skills. Strategic only - does not duplicate engineering data skills.