「evaluate」の検索結果

Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok.

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Evaluate agent behavior with versioned cases and explicit verifiers. Use when comparing agent or prompt changes, reproducing failures, or running agent regression tests.

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。

Evaluate everything the PA agent manages — tasks, skills, PA network health, billing, calendar connections, and memory quality. Use when: owner asks for an evaluation, wants to know what's working and what isn't, or requests a performance report. Combines supervisor status with quality scoring.

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。

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.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。

Evaluate recommender system quality for the CSX4207 Vinyl Record Store. Use whenever you must compute or report recommender metrics (Precision@k, Recall@k, HitRate@k, MRR, MAP@k, NDCG@k, coverage, diversity, novelty, serendipity, personalization), design an evaluation protocol/split, run a baseline comparison, or write the evaluation section of a course deliverable. Covers formulas, JavaScript reference implementations, and the reporting checklist.

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。

Evaluate and improve AI-generated output with explicit rubrics, reflection loops, and stop conditions. Use when building self-critique workflows, evaluator-optimizer pipelines, or acceptance gates for code, docs, analysis, or plans.

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。

Understand the constraints a design was built under and evaluate quality within that context. Use when reviewing work that had limited time, budget, or team size, or when assessing whether constraints were handled well.

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。

Break a design system into its constituent decisions and evaluate each one. Use when auditing design systems, evaluating consistency, or understanding how a product maintains quality at scale.

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。

Design and evaluate programmatic SEO strategies for creating SEO-driven pages at scale using templates and structured 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。

When the user wants to design, optimize, or evaluate App Store screenshots and preview videos. Also use when the user mentions "screenshots", "app preview", "product page design", "screenshot design", "creative assets", or "what should my screenshots show". For A/B testing screenshots, see ab-test-store-listing. For full ASO audit, see aso-audit.

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。

When the user wants to discover, evaluate, or prioritize App Store keywords. Also use when the user mentions "keyword research", "find keywords", "search volume", "keyword difficulty", "keyword ideas", or "what keywords should I target". For implementing keywords into metadata, see metadata-optimization. For auditing current keyword performance, see aso-audit.

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 a 3-leg evaluation against a newly released LLM. Leg 1 is trap questions with deterministic answers, leg 2 is an agentic orchestration task with a planted failure, leg 3 is a brownfield feature build in a real repo. Use when the user wants to vibe-check, test, evaluate, or compare a new frontier model, or mentions model-bench, model vibe check, or launch-day protocol.

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。

Helps detection engineers identify coverage blind spots in system command execution detection rules, evaluate bypass risks, and reduce false negatives. Strictly limited to system command execution rules; not applicable to browser credential theft or abnormal process creation without command semantics.

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Use when: 'intake this repo/skill', 'evaluate external skill', 'should we adopt X', a candidate repo URL plus an adoption question, or any external skill/workflow/tool surfaces as a possible fit for Agistra. Structured front-door evaluation of external skills, workflows, and similar capability artifacts before any install, promotion, or adaptation decision. Ends in exactly one classification: Install candidate, Adapt concept, or Reject. Never install first — intake first.

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。

Evaluates code against Apple's App Store Review Guidelines. Use this skill when reviewing iOS, macOS, tvOS, watchOS, or visionOS app code (Swift, Objective-C, React Native, or Expo) to identify potential App Store rejection issues before submission. Triggers on tasks involving app review preparation, compliance checking, or App Store submission readiness.

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This skill should be used when the user asks to "perform vulnerability scanning", "scan networks for open ports", "assess web application security", "scan wireless networks", "detect malware", "check cloud security", or "evaluate system compliance". It provides comprehensive guidance on security scanning tools and methodologies.

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。

When the user wants to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness. Also use when the user mentions "engineering as marketing," "free tool," "marketing tool," "calculator," "generator," "interactive tool," "lead gen tool," "build a tool for leads," or "free resource." This skill bridges engineering and marketing — useful for founders and technical marketers.

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 "test for broken authentication vulnerabilities", "assess session management security", "perform credential stuffing tests", "evaluate password policies", "test for session fixation", or "identify authentication bypass flaws". It provides comprehensive techniques for identifying authentication and session management weaknesses in web 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。

Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok.

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。

Assesses organizational readiness for post-quantum cryptography migration per NIST FIPS 203/204/205 standards. Performs cryptographic inventory scanning to identify quantum-vulnerable algorithms (RSA, ECDH, ECDSA), evaluates hybrid TLS configurations with X25519MLKEM768, and validates CRYSTALS-Kyber (ML-KEM) and CRYSTALS-Dilithium (ML-DSA) readiness. Implements crypto-agility assessment using oqs-provider for OpenSSL. Use planning yaparken or executing the transition from classical to post-quantu...

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Kubernetes penetration testing systematically evaluates cluster security by simulating attacker techniques against the API server, kubelet, etcd, pods, RBAC, network policies, and secrets. Using tools

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。

Hash cracking is an essential skill for penetration testers and security auditors to evaluate password strength. Hashcat is the world's fastest password recovery tool, supporting over 300 hash types w

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。