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Developer personality portrait generator. Supports subcommands: (1) 'generate my portrait' / 'analyze my personality' — full analysis; (2) 'update my portrait' — incremental update since last analysis; (3) 'install persona from <url>' — install community persona from GitHub; (4) 'list personas' / '我安装了哪些人格' — show installed; (5) 'remove persona <id>' — uninstall; (6) 'think like <name>' / '像<name>一样思考' — activate a persona. Also triggers on 'vibe-portrait', 'what kind of developer am I'.

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Use when the user asks "who are our customers?" / "how do we tailor for X stakeholder?" / "who should this report go to?", or wants to map / re-map stakeholder needs. Ensures intelligence reaches the right people in the right format.

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Indicator pivoting methodology — how to use one known indicator to discover related infrastructure across the IOC graph. Decision tree by indicator type with concrete `/lookup-*` commands per pivot, a worked multi-hop example, pivot-quality scoring, and routing into the rigor pipeline. Use when the user asks "what else is connected to this IP / domain / hash / cert / actor?", needs to expand a single seed IOC into a campaign cluster, or wants the canonical reference for graph-walking IOCs.

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Use when assessing the maturity of a CTI programme, the user asks "how mature is our CTI?" / "what should we improve next?", or wants a benchmark against the five-level model across six dimensions.

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Use when the user asks about ISAC participation, TAXII feeds, MISP communities, FIRST, STIX-based sharing, or how to publish intelligence externally. Covers sharing models, standards, communities, and TLP-governed dissemination.

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Use when the user asks about the CTI Hyperloop framework, the intelligence lifecycle as a high-tempo loop, or how to map intelligence work across strategic / operational / tactical levels with bidirectional feedback. Liberty91's operational doctrine.

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Use as the default entry point for any CTI request that doesn't name a specific skill. Activates when a user asks to investigate an indicator, profile a threat actor, write an assessment, enrich IOCs, or build detection rules, and when a user asks where a report or article comes from, how reliable it is, to grade a source, check a report, or split a report into claims, or pastes a bare article URL. Routes to the right investigation, provenance, grading or analysis skill, then auto-applies rigor skills (source rating, TLP, confidence, likelihood) on the output.

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Use when the user wants to configure API keys for the CTI skills pack, asks "how do I set up keys", "configure VirusTotal", "add my Shodan key", or runs /cti-setup. Walks through API key configuration inside Claude Code without needing to run a shell script. Also handles re-running setup, adding individual keys, and verifying that configured keys work.

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Use when assigning a confidence level to an analytical judgment, the user asks "how confident are we?" / "what is the confidence on X?", or the orchestrator's tradecraft pipeline calls for a confidence level before publishing. Provides three named levels (High, Moderate, Low) with 0-100 score ranges aligned to STIX, and the rule that confidence cannot exceed what the weakest load-bearing claim supports.

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Use when you need to answer "which attacker techniques do our controls actually stop, and how well?", "what controls should I have for this threat?", or "what telemetry should I collect to detect it?" — joining a customer's or your own security control baseline to ATT&CK techniques using a public, versioned evidence base of 9,545 control-to-technique mappings from six sources. Produces four ranked lists (addressed strongly, addressed weakly, real gaps, and techniques no control anywhere addresses). Use for control gap analysis, security programme prioritisation, board reporting on coverage, or the Resistance Strength side of a FAIR risk assessment. Invoke after /threat-actor-profiling or /lookup-liberty91 has produced a technique list.

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Use when phrasing a forward-looking statement, the user asks "how likely is X?" / "what's the likelihood?", or the tradecraft pipeline applies a probability yardstick to a finished product. Standardised likelihood language across all products.

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Use when the user asks about initial access brokers (IABs), the access-listing market, ransomware-feeding-IAB pipelines, specific broker handles, or how access is priced and packaged. Self-updating knowledge cell.

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Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup

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Dispatch to the right problem-solving technique based on how you're stuck

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Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

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Tell the agent to zoom out and give broader context or a higher-level perspective. Use when you're unfamiliar with a section of code or need to understand how it fits into the bigger picture.

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Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains.

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This skill should be used when the model's ROLE_TYPE is orchestrator and needs to delegate tasks to specialist sub-agents. Provides scientific delegation framework ensuring world-building context (WHERE, WHAT, WHY) while preserving agent autonomy in implementation decisions (HOW). Use when planning task delegation, structuring sub-agent prompts, or coordinating multi-agent workflows.

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Execute this skill should be used when the user asks about "SPAWN REQUEST format", "agent reports", "agent coordination", "parallel agents", "report format", "agent communication", or needs to understand how agents coordinate within the sprint system. Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.

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Initialize or improve AGENTS.md files that define how coding agents operate in a repo. Use when asked to set up or replace an agent init command (Codex, Claude), standardize multi-agent behavior, or audit an existing AGENTS.md for clarity, commands, boundaries, and repo-specific context. For Claude Code, also create CLAUDE.md as a symlink to AGENTS.md.

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Generate visual hierarchy diagrams of agent system showing levels and delegation. Use for documentation or onboarding.

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Inspect Orchestra projects and tasks, assign workers, queue planning, approve exact plans only on human instruction, request replanning with feedback, show stored PR linkages, reconcile receipts, and scope native agent/skill authoring. Orca-managed worktrees use the separate Orca CLI skill.

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"Apply the Theory of Planned Behavior to predict behavioral intentions from attitudes, subjective norms, and perceived behavioral control, and identify intervention leverage points. Use this skill when the user needs to predict adoption of a new behavior, diagnose why an intended behavior does not occur, design behavior change campaigns, or when they ask 'why do people not follow through', 'what predicts behavior change', or 'how to increase adoption rates'.".

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"Apply Sociotechnical Systems Theory to analyze and design work systems through joint optimization of social and technical subsystems. Use this skill when the user needs to diagnose why a technology implementation disrupted work practices, design IT-enabled work systems that balance human and technical needs, or when they ask 'why did this system hurt productivity despite being technically sound', 'how do we design work around new technology', or 'why are people resisting this technically superior system'.".

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。