545 件 ・ 関連度順
概要と使いどころ
Execute advanced LLM Jailbreaking techniques using roleplay, nested environments (virtual machines), and complex personas to completely bypass safety constraints and ethical alignments embedded in AI models.
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。
Identify and exploit GraphQL API vulnerabilities by leveraging Introspection queries to dump the entire database schema, performing query batching to bypass rate limits (brute forcing), and extracting deeply nested unauthorized data via graph relationship abuse.
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。
API authorization and BOLA testing playbook. Use when APIs expose object identifiers, nested resources, hidden writable fields, or weak function-level authorization.
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。
Open the warm channel for a role the pipeline already assessed. Finds who the user already knows at the company, researches named targets from public professional presence when they know nobody, grades each path honestly, drafts the ask through the voice agent, and writes the contacts into the Referrals table in job_search.md.
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。
Anti-AI-slop design system for distinctive, premium interfaces. Bold typography, dark-first #060610, fluid clamp() type, cascade layers + native nesting + container queries, OKLCH color, @starting-style, View Transitions API, DTCG tokens.
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。
Client-side routing with data APIs — loaders, actions, error boundaries, search params, nested layouts, and code splitting
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。
Offline time-stretch / pitch / varispeed — character modes, fine-tune presets, A/B toolkit, and the honest quality state, so an agent can pick a mode, dial it in, and ship a plugin with it.
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。
Ask Daniel a blocking decision as options with a recommendation and honest pros/cons, rather than prose. Use whenever work is blocked on a judgment call, a product decision, an approval, or a choice between approaches — instead of writing "let me know which you prefer" at the end of a message.
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 whenever the user asks you to act as, consult, or reason like a specific job role/domain expert (e.g. "review this like a CFO," "what would a UX designer say," "act as a contracts lawyer") and this repo's roles/ directory is available. Finds the best-matching role SKILL.md and adopts it, or honestly reports the gap if none exists.
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。
Query and answer questions about Volcengine API specifications. Use when the user asks about API parameters, error codes, request methods, enum values, required fields, response structures, pagination, parameter dependencies, service capability lists, API availability, or API comparisons, even if they do not explicitly say "API". Typical intent includes checking what an action supports, which fields are required, what values a parameter accepts, why an API returns a specific error, how to pass nested or body parameters, how pagination works, what an API response contains, whether a batch operation exists, what services or versions expose an operation, or how two APIs differ. Use API Explorer data as the authoritative source and preserve constraints, examples, and caveats found in the spec. Answer in Chinese or English. When the user needs runnable SDK code, language-specific examples, or SDK configuration, hand off to volcengine-sdk-generator. When they need CLI operations, hand off to volcengine-cli.
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 for BayeSED3 SED work — galaxy or AGN fitting, prior setup, Results and posterior plots, Bayesian evidence or model-configuration comparison, MultiNest or advanced run modes (AB mag, phot/spec-only). Trigger immediately on vague asks like "how do I fit this galaxy?"
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。
Apply the devil's advocate technique: structured critical thinking that stress-tests ideas, plans, and decisions. Use when you need honest critique before committing to something important.
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。
Run structured design critiques with frameworks for feedback that is honest, specific, and actionable.
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。
Write readable, maintainable code: naming, small functions, clear control flow, and honest abstractions. Use when writing new code, refactoring, or reviewing for readability.
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。
Working with observational climate data — reanalyses, station records, anomalies, trends, and honest uncertainty.
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。
Bayesian data analysis — priors, likelihoods, posterior computation, model comparison, and honest reporting.
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。
Writing biosketches that build reviewer confidence — personal statement, contributions, and honest positioning.
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。
Generate OpenAPI 3.1 documentation from your API codebase. Auto-detects Express, Fastify, NestJS, Django, FastAPI, Flask, Rails, Spring, Go, and more. Triggers: you need API documentation, OpenAPI spec, Swagger docs, endpoint reference, or REST API docs.
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。
Deliver feedback using Kim Scott's Radical Candor framework - care personally while challenging directly. Use when a leader needs to give difficult feedback, says "I need to tell someone something hard", "how do I give feedback without hurting them", "I've been avoiding a conversation", "my direct report isn't performing", "someone on my team has a blind spot", "I keep sugarcoating things", or "how do I be honest without being a jerk". Also trigger when someone describes being too nice (ruinous empathy) or too harsh (obnoxious aggression), or when they describe avoiding a conversation they know they need to have.
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 this skill when setting up or modifying product bundles, product options, product rules, configuration attributes, and product features in Salesforce CPQ. Trigger keywords: CPQ product bundle, product rule, option constraint, feature configuration, dynamic bundle, filter rule, configuration attribute, bundle nesting. NOT for plain Products and Pricebooks without CPQ — use admin/products-and-pricebooks. NOT for moving an existing CPQ catalog between orgs — use data/product-catalog-migration-cpq. NOT for price rules, price actions or discount schedules — use admin/cpq-pricing-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。
The GraphQL pipeline for SKMTC generators — authoring generators whose input schema is GraphQL SDL rather than OpenAPI. Covers `toGqlOperationEntry`, `GqlOperation`, `synthesizeArgsObject` (mutation args -> object schema), the GQL enrichment routing (`[id][rootKind][fieldName][variant]` — two nested subject keys where OAS has path+method), the `to<Lang>GqlOperationProjectionBase` companion factories, and the `GeneratorKey` shape `id|rootKind|fieldName|variant`. Use this skill ALONGSIDE `skmtc-generator` whenever the schema source is GraphQL SDL or the task mentions "GraphQL", "SDL", "GqlOperation", "toGqlOperationEntry", or GraphQL query/mutation generators. Engine rules (producers, register/insert, the axioms) stay in `skmtc-generator`; this skill carries only what differs for GraphQL.
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。
Abductive reasoning about causes. Takes a phenomenon, separates observations from interpretations, then spawns diagnosticians applying different reasoning lenses (technical, human-factors, process, incentive-structure, environmental, temporal, measurement-artifact, statistical) in isolation. Orchestrator evaluates candidate causes for fit-against-evidence, calibrates confidence honestly, and reports leading candidate(s) with distinguishing evidence needed. Produces feedback only — no code, no tickets, no artifacts.
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。
Checks cyclomatic complexity, nesting, long methods, god classes, method signatures, O(n²), N+1 queries, constants management. Returns findings.
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。
This skill should be used when the user asks to "implement a DiD regression", "run a staggered difference-in-differences", "set up an event study", "implement IV / 2SLS", "run a regression discontinuity design", "build synthetic control", "do propensity score matching", "test parallel trends", "run Honest DiD", "wild cluster bootstrap", "Callaway-Sant'Anna", "Sun-Abraham", "Bacon decomposition", "double machine learning", "debiased machine learning", "DML / DoubleML", "cross-fitting", "causal forest", "heterogeneous treatment effects", "ATE with ML controls", "which causal design fits my data", or needs causal-inference code, diagnostics, or identification writing in Python (StatsPAI), R, or Stata. Based on Scott Cunningham's Causal Inference: The Mixtape, with runnable validated templates, ML-based causal inference patterns, and Journal of Finance applications.
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。