157 件 ・ 関連度順
概要と使いどころ
Evidence-first ECC Tools burn and billing audit workflow. Use when investigating runaway PR creation, quota bypass, premium-model leakage, duplicate jobs, or GitHub App cost spikes in the ECC Tools repo.
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。
Scan projects for credential leaks, secrets in code, insecure patterns, LLM API key exposure, PII leakage to external AI services, and .env/.gitignore misconfigurations. Especially useful for data and API integrations, regardless of implementation language.
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 auditing or fixing prose that reads like a leaked reasoning transcript — dead design-session citations such as (decision N), audit item codes, or §N of uncommitted drafts; change narration such as "used to", "no longer", "this cut"; stack or review vantage ("a later PR in this stack", "rejected in review"); reviewer-addressed justifications; control-flow narration; or hedged planning residue in comments, JSDoc, docs, or Agent Notes.
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。
Test vector stores for embedding inversion, cross-tenant leakage, and poisoning.
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。
Reviews one SKILL.md against the format rules and returns a findings table: strict YAML front matter with exactly name and description, name equal to the folder, description as the trigger, the eight-heading skeleton, capability-neutral wording, safety boundaries. Each finding carries severity, rule identifier, location, quoted evidence and replacement text; the verdict READY, REVISE or BLOCKED is an apparent state and the owner decides. Use when the user asks to "review this SKILL.md", "check my skill file before upload", "lint this skill description", "validate the front matter of this skill" or "score this skill folder". Do not use to write an agent's instructions field, use agent-instructions-drafter instead; for injection or leakage exposures use agent-instructions-red-team; for launch tests use agent-evaluation-plan. Drafts for human review; never approves, authorises or signs off.
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。
Designs a pre-launch evaluation plan for a declarative agent from its instructions text, skills, capabilities, knowledge sources and sample requests: a behaviour contract of testable statements quoted from the text, test prompts by scenario family and tier with setup, expected behaviour, pass and fail criteria and red flags, a red-flag catalogue, a blank scoring sheet, a coverage table and a go or no-go checklist the owner completes and decides. Use when the user asks to "write test cases for my agent", "how do I evaluate this agent before launch", "build a test plan for the agent", "what should I check before publishing this agent" or "give me a go no-go checklist". Do not use for finding injection or leakage exposures in the instructions, use agent-instructions-red-team instead; do not use for reviewing one SKILL.md, use skill-file-reviewer instead. Drafts for human review; never approves, authorises or signs off.
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。
Reviews the instructions text and skills of a declarative agent, with its stated capabilities, knowledge sources and audience, for prompt-injection exposure, data-leakage paths, over-broad permissions and missing refusals, and returns an attack-surface map, a findings table with severity, quoted evidence and attack path, one pasteable fix per finding, a probe pack the owner can run and a refusal-coverage table. Use when the user asks to "red-team this agent", "check these instructions for prompt injection", "could this agent leak data", "review the permissions on my agent" or "what should this agent refuse". Do not use for checking a SKILL.md against the format rules, use skill-file-reviewer instead; do not use for designing the launch test set, use agent-evaluation-plan instead. Drafts for human review; never approves, authorises or signs off.
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。
- Investigator OPSEC — threat-model who might notice you, control your attribution surface across IP, ASN, browser and TLS fingerprint, timing and logged-in accounts, separate research identity from… Use when setting up a research account, avoiding tipping off a subject, worrying about LinkedIn profile-view leakage, needing a burner phone or email, or hardening a research VM or browser profile
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 the user asks to "watch my list health over time", "flag decaying / unengaged subscribers on a schedule", "why is my open rate drifting down / bounces creeping up", or "build me a re-permission and prune worklist"; runs the scheduled SEND list-decay + suppression-drift watch — an engagement-recency cohort read (30/90/180/365-day), hard-bounce and spam-complaint trend vs benchmark, suppression-list growth/leakage check, and a segmented re-permission / sunset / prune worklist tied to SEND S (list hygiene) and E (engagement-decay) sub-items. Not for the one-time pre-send authentication pre-flight — use deliverability-qa; not for the consent/suppression record itself — use consent-registry; not for computing the EQS or enforcing vetoes — use email-quality-auditor. 邮件列表健康度监控/退订漂移/沉睡用户清理
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。
Tests WebSocket API implementations for security vulnerabilities including missing authentication on WebSocket upgrade, Cross-Site WebSocket Hijacking (CSWSH), injection attacks through WebSocket messages, insufficient input validation, denial-of-service via message flooding, and information leakage through WebSocket frames. The tester intercepts WebSocket handshakes and messages using Burp Suite, crafts malicious payloads, and tests for authorization bypass on WebSocket channels. Activates f...
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。
Implement API schema validation using OpenAPI specifications and JSON Schema to enforce input/output contracts and prevent injection, data exposure, and mass assignment attacks.
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。
Tests API authentication mechanisms for weaknesses including broken token validation, missing authentication on endpoints, weak password policies, credential stuffing susceptibility, token leakage in URLs or logs, and session management flaws. The tester evaluates JWT implementation, API key handling, OAuth flows, and session token entropy to identify authentication bypasses. Maps to OWASP API2:2023 Broken Authentication. Activates for requests involving API authentication testing, token vali...
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。
Tests OAuth 2.0 and OpenID Connect implementations for security flaws including authorization code interception, redirect URI manipulation, CSRF in OAuth flows, token leakage, scope escalation, and PKCE bypass. The tester evaluates the authorization server, client application, and token handling for common misconfigurations that enable account takeover or unauthorized access. Activates for requests involving OAuth security testing, OIDC vulnerability assessment, OAuth2 redirect bypass, or aut...
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。
Implements secure API key generation, storage, rotation, and revocation controls to protect API authentication credentials from leakage, brute force, and abuse. The engineer designs API key formats with sufficient entropy, implements secure hashing for storage, enforces per-key scoping and rate limiting, monitors for leaked keys in public repositories, and builds key rotation workflows. Activates for requests involving API key management, API key security, key rotation policy, or API credenti...
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。
Implements input and output validation guardrails for LLM-powered applications to prevent prompt injection, data leakage, toxic content generation, and hallucinated outputs. Builds a security validation pipeline using NVIDIA NeMo Guardrails Colang definitions, custom Python validators for PII Tespit and content policy enforcement, and the Guardrails AI framework for structured output validation. The guardrails system intercepts both user inputs (blocking injection attempts, stripping PII, ...
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。
Comprehensive LLM security testing: bias detection, data leakage, prompt injection, jailbreak, alignment testing, adversarial prompts
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。
Selects biomarker features from high-dimensional omics data using Boruta all-relevant selection, mRMR, LASSO/elastic-net, and stability selection, while controlling the leakage, irreproducibility, and correlated-feature traps that make most published signatures fail to replicate. Use when identifying candidate biomarkers, deciding between an all-relevant and a minimal-optimal selector, or judging whether a selected gene set is reproducible. For unbiased performance estimation of the resulting model see machine-learning/model-validation; for interpreting a trained model see machine-learning/prediction-explanation.
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。
End-to-end biomarker discovery workflow from expression data to validated biomarker panels. Covers feature selection with Boruta/LASSO, leakage-safe cross-validation, calibration, and SHAP interpretation. Use when building and validating diagnostic or prognostic biomarker signatures from omics data.
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。
Decision-grade statistical analysis for metabolomics intensity tables. Covers transformation and scaling (Pareto vs unit-variance as a hidden hypothesis), unsupervised structure (PCA/HCA for QC), permutation-validated PLS-DA/OPLS-DA (R2 vs Q2, double CV, VIP as heuristic), univariate testing (Welch/Mann-Whitney/ANOVA/LMM with covariate adjustment), and dependence-aware multiple testing. Use when testing which metabolites differ, building or validating a discriminant model, choosing a scaling, or correcting many correlated tests. For sample-wise normalization/drift correction see metabolomics/normalization-qc; for ML classifiers and selection-inside-CV leakage see machine-learning/biomarker-discovery and machine-learning/model-validation; for pathway interpretation see metabolomics/pathway-mapping; for design/power/multiplicity regime see experimental-design/multiple-testing.
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。
Comprehensive PR code review for OneKey monorepo. Use when reviewing PRs, code changes, or diffs — covers security (secrets/PII leakage, supply-chain, AuthN/AuthZ), code quality (hooks, race conditions, null safety, concurrent requests), and OneKey-specific patterns (Fabric crashes, MIUI, BigNumber). Triggers on "review PR", "review this PR", "code review", "check this diff", "审查 PR", "代码审查", "review
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。
Harden LLM and agent integrations you operate: prompt injection, tool allowlists, secret leakage, and supply-chain of models. Defensive only.
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。
Analyzes a multi-step conversion funnel to find where users drop off and which steps have the worst leakage. Use this skill when someone describes a journey or funnel and asks about conversion rates, drop-off, fallout, or step completion. Trigger for phrases like "analyze our onboarding funnel," "where are users dropping off," "what's our checkout conversion rate," "funnel analysis," "show me fallout between these steps," or "which step loses the most users."
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。
Analyzes a multi-step conversion funnel to find where visitors drop off and which steps have the worst leakage. Use this skill when someone describes a journey and asks about conversion rates, drop-off, fallout, or step completion. Trigger for "analyze our checkout funnel," "where are visitors dropping off," "what's our add-to-cart to purchase conversion rate," "funnel analysis," "show me fallout between steps," or "which step loses the most visitors."
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。
Detects leaky abstractions in PHP code. Identifies implementation details exposed in interfaces, concrete returns from abstract methods, framework leakage into domain, and infrastructure concerns in application layer.
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。