326 skills · sorted by relevance
Plan a Claude Managed Agent around one clear job, then route work through setup, launch preparation, evaluation, and scheduling. Produce execution plans and curl commands that users run with their own Anthropic API key.
Scope a Claude Managed Agent through six questions about its job, trigger, inputs, actions, success criteria, and recurrence. Produce a validated build sheet with configuration components, deferred features, and an evaluation plan, without requiring an API key.
Trace application behavior and explain data structures using compact text tree diagrams. The diagrams connect user actions to real functions, data types, state changes, and the components that render again as a result.
Build Cloud Monitoring requests from metric definitions and resource details. Generate JSON parameters, filters, and aggregation settings for retrieving time series data, then validate the request against the live API.
Create reusable slash commands for Agent Zero using YAML configuration files paired with text templates or Python scripts. It helps choose project or global scope, update existing commands, and report the saved files and exact command to invoke.
Write large text files when write_file or shell_agent fails because of content size limits. The fallback passes multiline content through run_shell to Python, with guidance on escaping characters and checking the saved file.
Investigate insecure deserialization, where restoring objects from stored or transmitted data can execute unwanted code. Covers multiple languages, input format recognition, vulnerable processing points, verification methods, and documentation of affected libraries and entry points.
Plan and configure command and control (C2) systems for red team exercises. Covers major frameworks, communication methods, relay servers, certificate management, and the network or endpoint signals defenders use to detect these systems.
Review how evidence can be altered during authorized security exercises on Windows and Linux. Covers logs, timestamps, memory, disk records, and network traces, alongside the signs defenders use to detect manipulation.
Assess dependency confusion, where a build retrieves a public package instead of an intended private one. Discover internal package names, review registry settings, plan callback-based proofs of execution, and document fixes across major package ecosystems.
Support shellcode development for security testing: small machine-code programs executed in memory. The skill covers x86/x64 implementation, code that works regardless of its memory address, loaders, executable conversion, debugging, and platform-specific execution constraints.
Assess how applications use encryption, signed tokens, and random values. Identify implementation weaknesses, select relevant testing tools, and document causes and fixes for issues involving encryption modes, RSA parameters, predictable randomness, and key derivation.
Assess how Wi-Fi clients respond to impersonated access points using Evil Twin, KARMA, and Mana methods. Covers portal-based credential exposure, traffic interception conditions, client behavior, and limits imposed by modern protections.
Retrieve concise FinnGen association results for one genetic variant. Accepts rsID identifiers or GRCh37/GRCh38 genome coordinates, resolves the query format, and reports association counts, truncation, and optional raw output files.
Look up compound–target binding data in BindingDB using PDB or UniProt identifiers, or search for similar chemical structures. Receive concise summaries of matching records, with full API responses saved to a file when requested.
Assess AI products, agents, MCP servers, and skill packages through authorized security testing. It models access boundaries, tests injection and tool misuse, and produces evidence-based reports with business impact, defensive successes, and concrete remediation steps.
Use for TeamHarness message delivery details after a flow has decided a message must be sent: current-session reply, NO_REPLY, cross-room/cross-channel message tool payloads, PROJECT_REQUESTED task-room handoff, and requester replyRoute reports. Do not use to choose work mode, create rooms, delegate, check, or accept tasks.
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Hunt Next.js specific vulnerabilities — Server Actions arbitrary function execution, Middleware auth bypass via static asset paths, ISR cache poisoning, Image Optimization SSRF (/_next/image), RSC payload leakage, getServerSideProps injection, source map exposure, debug endpoint leakage. Use when target runs Next.js 13/14/15 or any React SSR framework.
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This skill should be used when the user asks to "use Metasploit for penetration testing", "exploit vulnerabilities with msfconsole", "create payloads with msfvenom", "perform post-exploitation", "use auxiliary modules for scanning", or "develop custom exploits". It provides comprehensive guidance for leveraging the Metasploit Framework in security assessments.
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Check the health of published EAS Updates: crash rates, install/launch counts, unique users, payload size, and the split between embedded and OTA users per channel. Use when the user asks how an update is performing, whether a rollout is healthy, how many users are on the embedded build vs OTA, or wants to gate CI on update health.
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Compatibility alias for the descriptive PyMC skill name. Delegate to the canonical local `pymc` payload while preserving route and README compatibility.
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Compatibility alias for OpenAI platform documentation guidance. Delegate to the canonical local `openai-docs` payload while preserving route compatibility.
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Scaffold a standalone RTVI CV microservice that plugs into VSS Search and Alerts profiles via Kafka mdx-raw. The shipped scaffold script is a YOLO26 reference implementation (ONNX, labels, custom parser required). Use when building a new perception microservice repo, validating the VSS integration contract, extending that scaffold for segmentation frame-mask payloads, or scaffolding with placeholders before customer YOLO26 assets exist. For swapping the detector in the stock vss-rt-cv container, use rtvi-cv-customize-model instead. Live DeepStream integration cannot run until the customer-supplied ONNX, labels file, and parser library exist.
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Run the PAIDF Orchestration Image Attribute Augmentation DAG on Kubernetes - person-crop clothing augmentation, attribute search, and augmented dataset generation. Select for requests about image attribute augmentation, person attribute search, person re-identification data, clothing augmentation, attribute captions, augmentation payloads, run status, or result retrieval. Runs environment setup first when controller readiness is unknown. Not for video or defect-image generation.
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