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abdulyasir100

@abdulyasir100 source repo

9 published skills

  1. ▌
    Fusion · abdulyasir100 bundle
    Answer a hard question by fanning it out to a PANEL of models running in parallel — each answering independently with web search and bash, none seeing the others' work — then having Opus 4.8 judge every response into a structured analysis (consensus, contradictions, partial coverage, unique insights, blind spots) and write a final answer grounded in it. The panel is two independent Opus 4.8 runs (slug opus4.8-4.8), Opus 4.8 + GPT-5.5 via codex (opus4.8-gpt5.5), or those plus Gemini 3.1 Pro (opus4.8-gpt5.5-gemini3.1pro). Opus always judges and writes the final answer — the pipeline can't be reversed. Use this whenever the user asks to "run it through Fusion", wants a multi-model / panel / ensemble answer, wants a question cross-checked across models, or wants a higher-confidence answer with consensus and blind spots surfaced — even if they don't say "fusion". Best for high-stakes research, design calls, and debugging where being confidently wrong is expensive.
    0 installs
  2. ▌
    Debug Pro · abdulyasir100
    Systematic 7-step debugging methodology with language-specific debugging commands for JavaScript/TypeScript, Python, Swift, CSS, network, and git bisect. Includes common error pattern reference and quick diagnostic commands.
    0 installs
  3. ▌
    Cc Godmode · abdulyasir100
    CC_GodMode v5.11.3 - Self-orchestrating multi-agent development workflows. Delegates tasks to 8 specialized agents: researcher, architect, api-guardian, builder, validator, tester, scribe, and github-manager. Automates new features, bug fixes, and API changes with dual quality gates.
    0 installs
  4. ▌
    Skill Audit · abdulyasir100
    Audit installed Clawdbot/MCP skills for security risks using SkillLens. Detects exfiltration, execution, persistence, privilege bypass, prompt injection, and overbroad triggers. Produces risk-scored reports with concrete evidence.
    0 installs
  5. ▌
    Animated Web Design · abdulyasir100 bundle
    Build visually stunning, animation-rich websites with cinematic-quality motion design. Use this skill whenever the user wants to create a website, landing page, portfolio, product page, or any web UI that should look impressive and feel alive. Also use when the user mentions animations, transitions, scroll effects, parallax, carousels, hover effects, layered designs, or says things like "make it look premium", "I want something beautiful", "cinematic feel", "not generic", or "high-end design". This skill prevents generic AI-generated website aesthetics and produces distinctive, hand-crafted-feeling interfaces with real motion design craft.
    0 installs
  6. ▌
    Senior Data Engineer · abdulyasir100
    Production-grade data engineering expertise. Covers ETL/ELT pipeline design, batch vs streaming architecture, data modeling (dimensional, data vault), quality frameworks (Great Expectations, dbt tests), Spark tuning, Airflow/Prefect orchestration, and Kafka streaming patterns.
    0 installs
  7. ▌
    Hugging Face Datasets · abdulyasir100
    Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.
    0 installs
  8. ▌
    Senior Data Scientist · abdulyasir100
    Production-grade data science and ML expertise. Covers statistical modeling, A/B testing, causal inference, time series, ML deployment with monitoring and drift detection, real-time inference optimization, and end-to-end ML pipelines with Python, PyTorch, TensorFlow, and Scikit-learn.
    0 installs
  9. ▌
    Fast Claude CLI Generation · abdulyasir100
    Reduce latency when an app calls the `claude` CLI as a subprocess (Sonnet or any model) — faster AI turns / responses without changing the model. Use when generation "feels slow", a Claude-CLI-backed app lags, someone compares it unfavorably to a local LLM, or you're asked to speed up / optimize per-call LLM latency, time-to-first-token, or throughput. Logic and decision order only — not implementation. Distilled from a real optimization that cut median latency ~30% and killed random multi-second freezes with no quality loss.
    0 installs