3.1K skills · sorted by relevance
Apply behavioral science to marketing pages, pricing, ads, and customer journeys. Use a catalog of over 70 mental models to diagnose barriers to action and develop concrete recommendations suited to the audience and goal.
Turn company values into observable workplace behaviors. Develop a culture code, a document explaining how the company operates, design anonymous culture surveys, and choose recurring practices suited to the organization's size and growth stage.
Create a GitHub tracking issue from a merged Kilo v1 pull request, documenting behavior, edge cases, and acceptance criteria so an agent can verify or rebuild the same behavior in opencode v2.
Investigate errors, failing tests, or slow behavior and explain the causal chain with source file and line references. Deliver diagnosis alone or apply a verified fix, starting with a test that reproduces the defect.
Drives a CARLA vehicle to a specific destination using navigation agents that plan routes, avoid obstacles, and obey traffic lights. Can also plan and draw a route between two points without moving the vehicle.
Customize windows in macOS SwiftUI apps, including titles, toolbars, drag areas, sizing, placement, and restoration. It helps give main windows, utility panels, and media players behavior suited to their purpose.
Reproduce and verify Weave Router behavior locally with Docker Compose and Claude CLI. Test model routing, response conversion, and streaming against real APIs or a mock service, then inspect logs without changing global Claude Code settings.
Add an agent execution engine to gh-aw using a shared Markdown definition where possible. The skill guides installation, authentication, configuration, and testing, with Go infrastructure changes reserved for capabilities that existing settings cannot express.
Design NPC and enemy decision-making with finite state machines, behavior trees, steering behaviors, and A* pathfinding — engine-neutral algorithms that pair with the detected engine's navigation API. Use when building enemy AI, an FSM or behavior tree, steering/flocking, or pathfinding, or when the user mentions state machine, behavior tree, blackboard, A*, navmesh, seek, or patrol/chase.
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Use when a complex or risky code change should be split into Kent Beck's two-step method by first making the change easy through behavior-preserving preparatory refactoring, then making the intended behavior change once the design supports it. This should trigger for requests such as Apply two-step change; Make this risky change safer; Refactor before changing behavior; Separate preparation from behavior change. Part of Plinth Toolkit
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Use when a Java change needs independent Behavior-Driven Development guidance from trusted behavior facts through concrete examples and observable scenarios, with focused clarification when behavior is pending or ambiguous. This should trigger for requests such as Apply BDD; Facilitate behavior examples; Discover scenarios with Given When Then; Review these examples for shared domain language; Complete BDD discovery as a self-contained interaction. Part of Plinth Toolkit
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Compare behavior across multiple versions of programs or repositories. Use when you need to analyze how functionality changes between versions, identify regressions, compare outputs and exceptions, or validate upgrades. The skill compares execution behavior, test results, outputs, exceptions, and observable states across versions, generating detailed reports showing behavioral divergences, potential regressions, added/removed functionality, and areas requiring validation. Supports multiple programming languages and can work with test suites or execution traces.
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Generate behavioral/feature documentation for web apps using code-first analysis. Reads source code via tree-sitting to produce _FEATURES.md, with optional visual verification via browser automation. Companion to tree-sitting. Use when documenting app behavior, creating feature inventories, generating behavioral ground truth for agents, or before modifying UI code. Triggers on "map features", "document app behavior", "feature inventory", "what does this app do".
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> Formal oracle for behavioral equivalence via bisimulation games. Triggers: behavioral equivalence check, bisimulation game, are two systems equivalent, did a skill update preserve behavior, attacker-defender game, partition refinement, distinguishing trace. >>>>>>> origin/main
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Diagnoses and fixes Claude behavioral issues in system prompts and Projects using tested countermeasure templates. Use when "Claude is too verbose," "keeps hedging," "agrees with everything," "claims it did something it didn't," "won't use a tool," "fix Claude's output," "tune Claude's behavior," "Claude ignores my preferences," "adds unsolicited disclaimers," "uses too many lists." Covers ten tendencies: agreeableness (output-content + persistent-preference), hedging, verbosity, list overuse, fabricated precision, over-exploration, tool miscalibration (over- and under-triggering), LaTeX defaulting, editorial drift, self-referential fabrication. Also use when auditing a system prompt for behavioral calibration or recalibrating a pre-4.7 prompt, and when users describe recurring output problems without naming a tendency. Do NOT use for scoring a prompt's overall quality — use rootnode-prompt-validation if available.
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Runs a sample in an instrumented sandbox to observe behavior: process tree, file and registry changes, network activity, and persistence, then summarizes the behavioral report into capabilities and IOCs. Activates for requests to detonate a sample, do dynamic or behavioral analysis, or interpret sandbox output.
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Use when implementing new observable frontend behavior or fixing a behavior-changing bug where a failing test can describe the missing or incorrect behavior first. Apply to components, hooks/composables, utilities, API clients, route guards, or user workflows; pure behavior-preserving refactoring uses an already-green contract instead.
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Create custom directives in Angular v20+ for DOM manipulation and behavior extension. Use for attribute directives that modify element behavior/appearance, structural directives for portals/overlays, and host directives for composition. Triggers on creating reusable DOM behaviors, extending element functionality, or composing behaviors across components. Note - use native @if/@for/@switch for control flow, not custom structural directives.
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Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.
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Busabase App-in-Skill dashboard over a fixed, deterministic mock user-behavior funnel dataset (browse → search → compare → booking attempt/abandon → complete) for a generic consumer booking product. Use when the user invokes $kelly-behavior-predict or /kelly-behavior-predict, wants to review funnel drop-off, per-segment predicted next actions, or backtest a rule-based "predicted next action" heuristic against a mock historical sample. Fully deterministic mock data and a hand-recomputable rule — never a real ML/LLM model, never a live system.
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Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.
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Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.
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Reorganize existing OpenClaw documentation while checking behavior against source code, schemas, and tests. Preserve accurate details, move reference material to suitable pages, and verify formatting and links so readers can follow the main workflow.
Investigate unclear failures, intermittent behavior, and performance regressions before changing code. Separate symptoms from assumptions, trace how failures arise, and rank possible causes by evidence and ease of testing, then report the cause and supporting proof.