Produces a DRAFT product requirements document from the discovery notes, interview summaries, support themes, analytics notes and stakeholder messages the user provides: problem statement, target users, goals with measures as stated, numbered requirements each with a testable acceptance criterion, non-goals, constraints, dependencies and open questions, with every statement tagged evidenced, assumed or UNKNOWN so each assumption is visible for the product owner to confirm. Use when the user asks to "write a PRD", "draft the product requirements", "turn these discovery notes into requirements", "document what this feature needs to do" or "build the requirements doc for this epic". Do not use for supplier-facing requirements in a tender, use rfp-requirements-pack instead; for a technical design decision, use architecture-decision-record; for the change ticket that ships the work, use change-request-pack. Drafts for human review; never approves, authorises or signs off.
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kesslernity/awesome-copilot-agent-skills☆ 9Updated Sep 19, 2026
Convert Markdown documents to PDF. Two modes available — (1) Playwright-based conversion with Mermaid diagram support for technical documentation, and (2) fpdf2-based professional PDF generation with cover pages, themed styling, and business-quality table formatting for estimates, proposals, and reports. Use this skill when converting Markdown to PDF, generating business documents from Markdown, or converting Mermaid diagrams to images. Triggers on short phrases like "PDFに変換して", "markdownをpdfにして", "PDFにして", "PDF化して", "PDF出力して", "convert to PDF", "make a PDF", or any request involving converting content to PDF format.
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takusaotome/claude-skills-library☆ 9Updated Oct 5, 2026
Knowledge base from the FAA Systems Engineering Manual (SEM) v1.0.1. Use for civil-agency systems engineering as the FAA practices it inside the Acquisition Management System (AMS) and the National Airspace System (NAS): the five-phase AMS lifecycle and its decision points; operational concept development and implementation-free functional analysis (ConOps, FFBD/N², CMLs); requirements analysis and architectural design synthesis (PRS→MRS, the PRD ratchet pPRD→iPRD→fPRD, RAM, ISEF/DoDAF views, CPRs); the seven technical management disciplines (Integrated Technical Management/SEMP, Interface Management/IRD-ICD, Risk-Issue-Opportunity, Configuration Management, SE Information Management, Decision Analysis, Verification & Validation); and the specialty disciplines (RMA via Service Threads/STLSC, Life Cycle Engineering, E3/Spectrum, Human Factors, Information Security via the NIST RMF, System Safety via the SMS, and Hazardous Materials/Environmental/EOSH). Scope limits: this is FAA-specific guidance, not policy — it is a tailorable menu that points outward to companion handbooks (FAA-HDBK-006A for RMA, the SMS Manual, the NIST 800-series) rather than restating generic SE theory; it is thin on detailed cost estimating, contracting/FAR law, software-development methodology, named anti-pattern catalogues, and any non-FAA or non-civil-aviation lifecycle. Source has no page numbers in the extracted text (~360 pp.).
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jgsystemsconsulting/jgs-se-knowledge-packs☆ 8Updated Oct 15, 2026
Knowledge base from the NASA Digital Engineering Acquisition Framework Handbook (NASA-HDBK-1004). Use for acquiring digital/model-based data under contract: the Data Requirements Description (DRD) instrument and the Appendix A DRD suite (TDP, MBx, CDMP, CSA, CR, FCA/PCA, SDT, EMDAL, REF, MRI); the Data Type 1-5 control scale; SOW/RFP/Cost-Volume contract language and data rights (FAR/DFARS, Table 3 license categories); the Requirements Exchange Format (REF/ReqIF, UUID schema) and Master Records Index; model-based data definition (MBSE, CAD/PMI, M&S credibility, BOM, release-state mapping, PLM); digital data collaboration, the four owned architectures, and interoperability standards (MIL-STD-31000, STEP/ISO 10303, ASME Y14); the four MBE interoperability use cases; and MBE Plan development. Scope is the acquisition and contracting side of digital engineering. Does not reproduce ISO/STEP/ASME/MIL-STD/SAE standard text, and the companion NASA-HDBK-1009A carries the deeper digital-engineering practitioner detail this handbook defers to.
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jgsystemsconsulting/jgs-se-knowledge-packs☆ 8Updated Oct 15, 2026
Knowledge base from MIL-STD-881F (13 May 2022), DoD Standard Practice for Work Breakdown Structures for Defense Materiel Items. Use for Program/Contract/Subcontract WBS construction, 100% rule and dictionary discipline, commodity appendices A–J, Common Elements (K), sustainment CES reporting (L), Government ST&E (M), and RFP/post-award implementation. Technical planning & WBS and PM/measurement focus—not a cost manual substitute for CAPE policy.
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jgsystemsconsulting/jgs-se-knowledge-packs☆ 8Updated Oct 15, 2026
3D/motion QA: production-level FPS, reverse scroll, low power, reduced motion. Use when implementing, reviewing or testing 3d/motion qa for React, Vite, Next.js or Perfect_AI projects.
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Realjustawall/Perfect-AI☆ 6Updated Oct 10, 2026
Search NHTSA vehicle recalls, FDA food/drug recalls, and CFPB consumer complaints. 3 tools for product safety monitoring.
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martc03/gov-mcp-servers☆ 6Updated Apr 6, 2026
AiZynthFinder retrosynthetic route planning (CASP) from AstraZeneca Molecular AI. Monte Carlo tree search guided by a template-based neural expansion policy recursively disconnects a target SMILES until precursors are found in a purchasable stock. Covers config.yml (v4 format), aizynthcli batch screening, the AiZynthFinder/AiZynthExpander Python API, one-step disconnections, custom stocks via smiles2stock, scorers, Retro*/breadth-first/DFPN search alternatives, and reading output.json.gz / trees.json. Use for synthesis route planning, synthesizability screening, and building-block/precursor search. For reaction barriers use neb-irc-activation-energy; for 2D reaction scheme drawing use rdkit-chemdraw-cdxml.
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bg-szy/TOP-SKILLS☆ 6Updated Sep 8, 2026
Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.
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bg-szy/TOP-SKILLS☆ 6Updated Sep 8, 2026
Turn a live app or landing page into a short launch video: composition brief, render in Hyperframes or Remotion, an ffprobe check per format, publish hand-off only after GO. Use for "launch video", "make a video of the shipped app", "promo clip for the landing page".
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hybridlabor-api/aos☆ 6Updated Oct 16, 2026
Turn a release or ship recap into a social pack: posts per platform where every claim traces to a facts file, clip cut-downs per aspect ratio cut with ffmpeg and checked with ffprobe, hand-off for publishing only after GO. Use for "social pack for the release", "posts and clips for this launch", "announce the release".
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hybridlabor-api/aos☆ 6Updated Oct 16, 2026
Generate Japanese PDFs using reportlab or fpdf2 with CJK font embedding, vertical text, business document templates, and inkan image placement. Triggers on requests to create 日本語PDF, 請求書PDF, 領収書PDF, PDF帳票, 縦書きPDF.
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LinkX-Japan/ai-souken-workflows☆ 6Updated Mar 12, 2026
Pushes interfaces past conventional limits with technically ambitious implementations — shaders, spring physics, scroll-driven reveals, 60fps animations. Use when the user wants to wow, impress, go all-out, or make something that feels extraordinary.
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waynesutton/teleprompter☆ 5Updated Jun 28, 2026
Build, analyze, repair, and audit finance three-statement models and operating forecasts. Use when the user invokes $kelly-finance, asks for 财务三表, 三表模型, income statement, balance sheet, cash flow statement, forecast model, budget model, financial projections, FP&A model, SaaS/unit economics forecast, fundraising model, board finance pack, investor model, model checks, balance-sheet balancing, cash runway, working capital, capex/depreciation schedules, debt schedules, scenario/sensitivity cases, or Excel/Sheets-ready finance outputs.
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mr-kelly/skills☆ 5Updated Oct 14, 2026
Spearphishing targets specific individuals using personalized, researched content that bypasses generic spam filters. Email security gateways (SEGs) like Microsoft Defender for Office 365, Proofpoint,
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micsapp/micstec-skills☆ 4Updated Mar 20, 2026
4 business growth agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Customer success (health scoring, churn), sales engineer (RFP), revenue operations (pipeline, GTM), contract & proposal writer. Python tools (stdlib-only).
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micsapp/micstec-skills☆ 4Updated Mar 20, 2026
Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.
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garochee33/DSH☆ 4Updated Oct 19, 2026
Post-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs FP16. Integrates with transformers and PEFT for QLoRA fine-tuning.
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huang-sh/DeepScience☆ 4Updated Jul 15, 2026
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
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huang-sh/DeepScience☆ 4Updated Jul 15, 2026
Chains a somatic (tumor-normal) SNV/indel and structural-variant pipeline end to end with GATK Mutect2 (or Strelka2), wiring the somatic-specific machinery - panel-of-normals and gnomAD germline-resource priors, GetPileupSummaries/CalculateContamination, and LearnReadOrientationModel FFPE/oxoG orientation-bias filtering fed into FilterMutectCalls. Use when calling somatic mutations from a tumor-normal pair (or tumor-only with PoN caveats), deciding which artifact filter removes which class of false positive, reasoning about VAF/purity/ploidy and clonal-vs-subclonal detection, adding somatic SV/CNV or TMB/MSI/signatures, or routing variants to AMP/ASCO/CAP tier and oncogenicity interpretation (never germline ACMG).
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huang-sh/DeepScience☆ 4Updated Jul 15, 2026
Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with HuggingFace Transformers.
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huang-sh/DeepScience☆ 4Updated Jul 15, 2026
Multi-method binding pocket detection and druggability assessment. Grid-based, fpocket, and P2Rank detection with druggability scoring, visualization, and cross-structure comparison.
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huang-sh/DeepScience☆ 4Updated Jul 15, 2026
Performs structure-based virtual screening using AutoDock Vina, SMINA, GNINA (CNN scoring), and DiffDock-L hybrid workflows with explicit choice rules across rigid vs flexible docking, cross-docking vs self-docking, binding-site detection (P2Rank, fpocket), receptor preparation (PDB2PQR, PROPKA), ligand preparation (meeko, OpenBabel), and ultralarge-library screening (ZINC22, Enamine REAL). Use when screening chemical libraries against a protein target to find candidate binders, ranking docking poses, or selecting a docking workflow for a specific scenario.
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huang-sh/DeepScience☆ 4Updated Jul 15, 2026
Performs molecular similarity searching using Tanimoto, Tversky, Dice, and cosine coefficients on bit/count fingerprints with explicit choice rules for symmetric vs asymmetric measures, scaffold-hopping vs lead-optimization regimes, activity-cliff diagnosis, and large-library nearest-neighbor methods (BulkTanimoto, Annoy MHFP6, USRCAT). Use when ranking compounds by structural resemblance to a query, clustering libraries, finding analogs, or diagnosing activity cliffs.
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huang-sh/DeepScience☆ 4Updated Jul 15, 2026