415건 · 관련도순
Establishes behavioral baselines from historical telemetry (process, network, or logon events) so hunts can flag rare and first-seen activity instead of relying on static signatures. Activates for requests to build a telemetry baseline, find rare or first-seen activity, or compute frequency baselines for anomaly hunting.
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Operationalizes a threat intelligence report into hunts: extracting IOCs and TTPs, mapping behaviors to ATT&CK and available telemetry, prioritizing durable behavioral indicators over volatile atomic ones, and producing concrete hunt queries. Activates for requests to hunt from a threat report, operationalize CTI, or turn an intel report into detections.
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Leveraged-prototype dev loop (`pulp loop`) — focus marker plus normal watch/rebuild loop, with AOT analyzer guidance and deferred ar-swap/PR-monitor playbook. Use when porting an existing UI/bundle to Pulp, doing visual/behavioral parity work, or batching upstream framework gap fixes.
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Use when a task needs the judgment of an Adapted Physical Education Specialist — writing a legally-defensible PE present level and annual goal from motor/fitness assessment data, choosing the right test battery and alternate items for a student's mobility profile, recommending a placement step on the PE least-restrictive-environment continuum, or distinguishing a motor/balance deficit from a behavioral avoidance pattern.
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Expert guidance for proactive threat hunting in Google SecOps. Use when proactively hunting for threats, retroactively analyzing indicators of compromise (IoCs), performing prevalence searches across enterprise events, hunting for MITRE ATT&CK techniques, or detecting behavioral and statistical outliers using UDM queries. Don't use for incoming alert triage (use secops-triage), active incident response and timeline deep-dives on a known breach (use secops-investigate), or detection rule authoring (use secops-detection-engineering).
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Behavioral guardrails against the six most common LLM coding failure modes: unstated assumptions, overbuilding, changes beyond the ask, no success condition, claiming done without output, and sprawling non-atomic changes. Use when writing, editing, reviewing or refactoring code, when the user says 'keep it simple', 'surgical change', 'don't over-engineer', 'minimal diff' or 'verify before saying done', or when a change keeps growing beyond the ask. For a full code review, see code-review.
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Test coverage quality analysis — behavioral coverage, critical gap identification, test resilience evaluation.
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เตรียมสัมภาษณ์งาน — STAR framework, behavioral Q&A, "เล่าเรื่องตัวเอง", 50 common Q, salary negotiation
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Analyze behavioral health outcome tracking systems for clinical measurement validity, treatment effectiveness, and provider performance comparison.
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Audit a student information system for dropout risk prediction. Analyzes attendance patterns, grade trajectories, behavioral indicators, early warning model accuracy, intervention tracking, equity in risk scoring, and socioeconomic factor integration..
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Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.
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AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
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Use this skill when designing, auditing, or troubleshooting behavioral boundaries for Agentforce agents — including topic (now subagent) Scope fields, agent-level system instructions, topic/action filters, the Escalation topic, restricted topics, and Instruction Adherence monitoring. Trigger keywords: agent guardrails, agent out of scope, restrict agent behavior, topic scope, subagent scope, agent fallback, Escalation topic, abuse prevention, action filters. NOT for Trust Layer content filtering (Einstein Trust Layer is a separate product concern), NOT for general topic routing design (use agentforce/agent-topic-design), NOT for prompt template construction (use agentforce/prompt-builder-templates).
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Use when defining or refining the tone, voice, and behavioral personality of an Agentforce agent: system instruction encoding, brand voice alignment, adaptive response formats, multi-persona strategies. NOT for writing the actual conversational copy — utterances, fallback messages, escalation phrasing — use admin/agent-conversation-design. NOT for topic scope design — use agentforce/agent-topic-design.
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Use this skill when designing or documenting a lead scoring model in Salesforce Sales Cloud or Account Engagement: qualifying criteria, MQL/SQL threshold definitions, scoring dimensions (demographic, firmographic, behavioral), and sales handoff SLA. NOT for configuring the scoring, grading, and automation rules in Account Engagement — use admin/mcae-lead-scoring-and-grading. NOT for the whole marketing program's lifecycle stages and platform scope — use admin/marketing-automation-requirements.
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Drafts a standalone API Acceptable Use Policy (AUP) for incorporation by reference into a master API license or terms-of-service agreement. Produces a publication-ready template with prohibited-use matrix, developer security checklist, graduated enforcement framework, AI/ML training restrictions, and versioning playbook. Trigger when a user needs to draft or update an API AUP, separate behavioral rules from core API terms, define prohibited API uses, add enforcement or change-management mechanics, or mentions acceptable use policy, developer security requirements, or API enforcement.
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Identify customers most likely to churn before they leave. Uses behavioral signals, usage patterns, and engagement data to score accounts and recommend retention actions.
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Deep behavioral security audit for AI agent skills and MCP tools. Performs deterministic static analysis (AST + Semgrep + 15 specialized scanners), cryptographic lockfile generation, and optional LLM-powered intent analysis. Use when installing, reviewing, or approving any skill, tool, plugin, or MCP server — especially before first use. Replaces basic safety summaries with full CWE-mapped, OWASP-tagged, line-referenced security reports.
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Analyze meeting transcripts to identify communication patterns, behavioral insights, and actionable feedback for improving communication and leadership effectiveness.
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Prepares for hiring manager rounds at Staff+ (L6+) level — scope of impact, influence without authority, ambiguity navigation, mentorship, strategic thinking. Use when practicing HM rounds or calibrating story depth for target level. Activate on "hiring manager round", "HM screen", "staff level", "scope of impact". NOT for coding interviews, system design, behavioral/values rounds, or resume writing.
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Describe patterns that may indicate bad-faith or manipulative communication including gish gallop, whataboutism, tone policing, motte-and-bailey, sealioning, lying by omission, deflection, and strategic evasion. Use when the user suspects manipulation, notices repeated non-engagement, wants to analyze debate tactics, or mentions 'bad faith', 'deflection', 'manipulation', 'dodging the question', 'avoiding the issue', 'gaslighting', 'moving goalposts'. Describes behavioral patterns without making psychological diagnoses.
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Prepare for Anthropic-specific technical interviews covering Constitutional AI, RLHF, interpretability, scaling laws, MCP, agentic systems, and AI safety. Activate on "anthropic interview", "constitutional AI prep", "alignment interview", "safety interview", "RLHF opinion", "interpretability prep", "anthropic technical". NOT for general ML interview prep, system design interviews, coding challenges, or behavioral interview practice.
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Use this skill when working with Brain Imaging Data Structure (BIDS) datasets: organizing neuroscience and biomedical data (MRI, EEG, MEG, iEEG, PET, microscopy, NIRS, motion capture, EMG, MR spectroscopy, behavioral), querying BIDS layouts, validating compliance, converting DICOM to BIDS, writing metadata sidecars, or creating BIDS derivatives.
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Multi-pass structural code review with adversarial personas. Input: branch diff (default), PR #123, commit, --pending. Use for 'review this PR/diff'. NOT for behavioral verification (mk:evaluate).
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