'files' 검색 결과

Author/validate/export Google's DESIGN.md token spec files.

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Operating discipline distilled from Claude Fable 5 for sessions and subagents on weaker models (Opus 4.x, Sonnet 5/4.x, Haiku 4.5) doing agentic coding. Load it at the START of any non-trivial task when not running on Fable 5: debugging, refactoring, changes across 2+ files, or unfamiliar code; and instruct a subagent on Opus/Sonnet/Haiku to read this skill with a non-trivial assignment. Triggers include "think like Fable", "fable-mode", "turn on discipline", "work carefully", dispatching a subagent on a weaker model, and repeated mistakes or rework in the session. NOT needed for trivial edits (rename, typo, one-liner) or purely conversational answers.

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Provides ASR (Automatic Speech Recognition) services via uwebasr.zcu.cz. Use this skill to transcribe audio files in multiple languages (CS, SK, EN, DE, PL, HU, HR, SR, NL) using state-of-the-art models like Zipformer.

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Auto-generate knowledge YAML from the codebase. Use when the user runs /sync-knowledge or wants knowledge files refreshed.

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Migrate test files from `as` assertions to @total-typescript/shoehorn helpers. Use when tests need partial fixtures, intentionally invalid data, or safer replacements for TypeScript assertions.

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Fact-check an implementation plan against the real codebase and first-party documentation, flagging inaccuracies with what / why / evidence and a severity tier. Use when the user wants a plan reviewed or validated for accuracy, runs /review-plan, or wants a plan checked against real code before implementing. Accepts a Beads issue, a filesystem path, or a plan pasted into chat.

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Answer questions about the codebase from knowledge files. Use when the user runs /ask or asks a domain/knowledge question about the repos.

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.NET testing fundamentals overview and navigation center. Triggered when users ask about "how to write .NET tests", ".NET testing getting started", "required testing tools", "testing best practices", "learn testing from scratch", and other general testing needs. Recommends appropriate sub-skills based on specific requirements, covering testing fundamentals, test data, assertions, mocking, special scenarios, and other 19 fundamental skills. Keywords: dotnet testing, .NET testing, testing getting started, how to write tests, testing best practices, unit test, unit test, xunit, 3A pattern, FIRST principle, assertion, assertion, mock, stub, NSubstitute, test data, AutoFixture, Bogus, validator, FluentValidation, TimeProvider, IFileSystem, code coverage, ITestOutputHelper, test naming

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Reads and modifies SDK-style .csproj files. PropertyGroup, ItemGroup, CPM, props.

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Containerizes .NET apps. Multi-stage Dockerfiles, SDK container publish (.NET 8+), rootless.

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Use as the single visible starter and controller for workspace work that may change files, runtime assets, planning state, docs, settings, or governance. Normalize the request into the Super Agent lifecycle: intake, spec registration for non-trivial work, planning registration, specialist routing, execution, testing, review, closeout, and planning-state updates before implementation begins.

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Documentation and narrative content for create-vue-dsfr. Use for markdown files, Storybook stories, VitePress guides, component documentation, and API documentation. Read the shared project skill before acting.

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Documentation and narrative content. USE FOR: writing docs; markdown files; storybook stories; vitepress guides; API documentation. DO NOT USE FOR: production code changes (use code-implementation skill); tests (use test-writing skill); commit conventions (use commit-conventions skill).

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Apply this site's visual identity — colours, type, logo files and fixed brand strings. Use for any page, component, social asset or document that should look like the site.

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Query, inspect, or refresh codebase intelligence files in .planning/intel/

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Review source files changed during a phase for bugs, security issues, and code quality problems

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Identifies and exploits insecure local data storage vulnerabilities in Android and iOS mobile applications including unencrypted databases, world-readable files, insecure SharedPreferences, plaintext credential storage, and improper keychain/keystore usage. Use when performing mobile penetration testing focused on OWASP M9 (Insecure Data Storage) or assessing compliance with MASVS-STORAGE requirements. Activates for requests involving mobile data storage security, local storage exploitation, SharedPreferences analysis, or mobile data leakage assessment.

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Detects and analyzes fileless malware that operates entirely in memory using PowerShell, WMI, .NET reflection, registry-resident payloads, and living-off-the-land binaries (LOLBins) without writing traditional executable files to disk. Activates for requests involving fileless threat detection, in-memory malware investigation, LOLBin abuse analysis, or WMI persistence examination.

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Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.

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Detects rootkit presence on compromised systems by identifying hidden processes, hooked system calls, modified kernel structures, hidden files, and covert network connections using memory forensics, cross-view detection, and integrity checking techniques. Activates for requests involving rootkit detection, hidden process discovery, kernel integrity checking, or system call hook analysis.

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Detect lateral movement in network traffic using Zeek (formerly Bro) log analysis. Parses conn.log, smb_mapping.log, smb_files.log, dce_rpc.log, kerberos.log, and ntlm.log to identify SMB file transfers, NTLM account spray activity, remote service execution, and anomalous internal connections.

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Detects fileless malware and in-memory attacks that execute entirely in RAM without writing persistent files to disk, evading traditional antivirus. Use when building detections for PowerShell-based attacks, reflective DLL injection, WMI persistence, and registry-resident malware. Activates for requests involving fileless malware detection, in-memory attacks, PowerShell exploitation, or living-off-the-land techniques.

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This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.

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Detecting exposed AWS credentials in source code repositories, CI/CD pipelines, and configuration files using TruffleHog, git-secrets, and AWS-native detection mechanisms to prevent credential theft and unauthorized account access.

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