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概要と使いどころ
Evaluates dividend policy with payout sustainability, peer comparison, and investor preference analysis across growth and value contexts. Use when analyzing dividend policy, evaluating payout ratios, or designing dividend programs.
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Validate a bug bounty finding before writing a report — the 7-Question Gate, 4 pre-submission gates, always-rejected list, conditional chain table, CVSS 3.1 quick reference, and severity decision guide. Use BEFORE writing any report to avoid N/A and low quality submissions.
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Hunt Insecure Direct Object Reference (IDOR) — test horizontal and vertical privilege escalation across user IDs, org IDs, tenant boundaries, and unguessable identifiers. Use when the user has an API endpoint with an identifier in the path/body that may be tested for unauthorized cross-user access.
日本語の概要は準備中です。原文の説明を表示しています。
Standards for authoring SDD plugin agents — frontmatter, self-containment, skill references, and no-user-interaction rules.
日本語の概要は準備中です。原文の説明を表示しています。
D2 diagramming language reference for architecture diagrams, sequence diagrams, grid layouts, SQL tables, and class diagrams. Produces .d2 files rendered via CLI or playground.
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Use when EZ_math_model multi or hybrid mode needs several domain-specialist subagents to gather outside knowledge, industry context, model theory, or sensitivity-analysis references in parallel.
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Use when EZ_math_model needs to read or convert PDF problem statements, extract text or tables from PDF attachments, summarize reference papers, or fall back when MinerU is unavailable.
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Use near the end of EZ_math_model intake when external/user-corpus contains user-provided papers, notes, PDFs, datasets, or examples that should become a local AGENTS.md reference index.
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Operating guide for construction project documents — load before reading drawings, specs, schedules, RFIs, submittals or bids. Data-access rules (never read PDFs directly; rasterize first), AgentCM graph-guided vision, drawing and cross-reference conventions, document precedence. Triggers: 'construction project', 'drawings', 'specs', 'sheet', 'RFI', 'submittal'.
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Scope-specific code gap analysis — extracts referenced codes from project docs, researches what should apply, surfaces the delta. Triggers: 'code research', 'what codes apply', 'code check', 'ADA requirements', 'egress'.
日本語の概要は準備中です。原文の説明を表示しています。
Maintain skills wiki health - check links, naming, cross-references, and coverage
日本語の概要は準備中です。原文の説明を表示しています。
Use when ingesting text samples to extract quantitative writing style metrics. Produces a structured JSON style profile with vocabulary patterns, sentence structure, tone markers, and formatting preferences. Invoke before voice-clone-generator to establish style constraints.
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Research-backed JSON Schema refresh workflow for updating existing schemas with validation checkpoints and cross-reference verification.
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Decision matrix for selecting multi-agent topologies (Supervisor, Swarm, Hierarchical, Conductor) with token economics, failure modes, and escalation paths
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Use when the user wants to search Turkish academic journals on DergiPark (keyword or advanced field search by title/author/abstract/DOI/ORCID/year/etc.), read a DergiPark article PDF as text, or extract an article's references — drives the user's own Chrome (no CAPTCHA solving needed) by injecting JavaScript.
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Spot-check citations in library files for obvious hallucinations. Resolves DOIs against the DOI registry, validates arXiv IDs, checks the format of journal references. Soft-fails on transient lookup failures rather than blocking. Recommended after kb-ingest and as part of periodic library hygiene.
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Run a Programme phase gate validator (requirements / design / test / code) against docs/specs/<feature-id>/. Block on missing artefact or broken cross-phase reference.
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Structure-based docking with AutoDock Vina, Vinardo, and AutoDock4 through the Meeko toolchain. Use this skill to define a docking box, prepare receptors and ligands as PDBQT, run single or batch docking, rescore, and interpret affinities, poses, and ligand efficiency. Covers box definition from a reference ligand or pocket residues, protonation and tautomer decisions, flexible side chains, exhaustiveness and seeds, redocking validation, and virtual screening over compound libraries. Also trigger on vina, smina, gnina, mk_prepare_ligand, mk_prepare_receptor, mk_export, scrub.py, PDBQT, autogrid4, docking box, or binding-pose prediction.
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Access a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design (RFdiffusion, ProteinMPNN, BoltzGen), antibody and nanobody design and developability, protein-ligand docking (DiffDock, Autodock Vina), binding-affinity prediction, MSA generation, and molecular dynamics. Use when the user mentions Tamarind or tamarind.bio, wants to run any of these open-source tools in the cloud, references app.tamarind.bio/api or the x-api-key header, or needs to submit batches of sequences for structural or biophysical characterization.
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How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
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This skill should be used when creating or editing notes inside an Obsidian-compatible vault, to write correct Obsidian Flavored Markdown — wikilinks, embeds, callouts, YAML properties (frontmatter), tasks, highlights, and block references. Use whenever writing .md notes for a second brain / Obsidian vault so links resolve and metadata is queryable.
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Reference WebGPU APIs, TSL syntax, node materials, WGSL integration, compute shaders, and post-processing in Three.js. For complete particle canvases use threejs-particle-canvas; for GLSL shaders use rocaille-shader. Triggers on TSL shader, WebGPU renderer, node material, WGSL, GPU compute, WebGPU setup.
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OpenAI GPT Image generation and editing (gpt-image-2, 1.5, 1, mini). Text-to-image, mask-based inpainting, multi-reference composition, multi-turn conversational editing via Responses API, streaming with partial images. This skill should be used when generating or editing images via OpenAI's image models, when near-perfect text rendering in images is needed, when mask-based region-aware editing is required, when multi-turn conversational image editing is desired, or when streaming progressive image delivery is needed. Complements nano-banana-pro (Gemini) as a parallel image generation backend.
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Generate and edit high-quality images using Google's Nano Banana Pro (Gemini 3 Pro Image) AI model. Use this skill when working with AI image generation or editing tasks including (1) Creating images from text prompts with professional quality, (2) Editing existing images with natural language instructions, (3) Multi-turn iterative image refinement, (4) Product photography and marketing visuals, (5) Creating infographics and diagrams with text, (6) Photorealistic and artistic image generation, (7) Batch image generation workflows, (8) Testing and troubleshooting Gemini image generation API. Supports up to 4K resolution, multiple aspect ratios, reference images, and advanced prompting techniques for cinema-quality results.
日本語の概要は準備中です。原文の説明を表示しています。