Use when configuring MCU sleep/stop/standby, WFI, STM32 PWR, nRF sleep, clock gating, wake-up EXTI sources, or measuring current draw. Not for the wake ISR: use interrupts-and-exceptions-baremetal.
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400건 · 관련도순
Use when configuring MCU sleep/stop/standby, WFI, STM32 PWR, nRF sleep, clock gating, wake-up EXTI sources, or measuring current draw. Not for the wake ISR: use interrupts-and-exceptions-baremetal.
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Use when writing no_std Cortex-M or RISC-V firmware in Rust with cortex-m-rt, probe-rs, defmt, RTIC, or a panic handler. Not for no_std library constraints: use rust-no-std.
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Use when writing a custom bootloader, jumping to application code, relocating VTOR, or implementing DFU/USB firmware update on Cortex-M. Not for reset-to-main: use baremetal-startup.
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Use when writing reset-to-main startup code, vector tables, VTOR, .data/.bss init, stack setup, startup.s, or crt0 for Cortex-M/RISC-V. Not for the bootloader jump: use bootloaders-embedded.
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Use when the user wants to run SQL - especially analytical SQL - on local files (parquet/csv/json), URLs, S3 paths, or remote databases (Postgres, MySQL, MongoDB, ClickHouse Cloud, Iceberg, Delta Lake) without setting up a server. Provides chDB - embedded ClickHouse SQL in Python with 1000+ functions, Session for stateful multi-step pipelines, parametrized queries, and cross-source joins via `s3()`, `mysql()`, `postgresql()`, `iceberg()`, `deltaLake()`, `remoteSecure()` table functions. TRIGGER when: user wants SQL on parquet/csv/files or across remote analytical sources; uses ClickHouse SQL features (window functions, windowFunnel, geoToH3, JSON path ops, Session, parametrized queries); imports `chdb` or calls `chdb.query()`. SKIP this skill for pandas-style DataFrame method-chaining (use chdb-datastore instead) or ClickHouse server administration.
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Verify which process actually owns a TCP port before assuming your fresh restart succeeded. Use when: (1) you killed an old server and started a new one but behaviour matches the OLD code/data, (2) `pkill -f pattern` returned 0 but old behaviour persists, (3) you embedded a new asset/binary but the served version is stale, (4) any "I just restarted X but I'm getting old results" situation. `pkill -f` matches against the process command line — if the live old process was started with `--port 0` (auto-assigned) and got the port you now want, the pattern won't match it. Always verify with `lsof -i :PORT` before debugging deeper.
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This skill should be used when the user asks "How do I...", "What is...", "How does X work in Prismatic?", "What's the best practice for...", wants to understand Prismatic concepts, features, or architecture, or needs guidance on marketplace deployment, customer connections, embedded UI, config pages, triggers, or other Prismatic product features. Search and retrieve documentation from prismatic.io/docs and reference examples from github.com/prismatic-io/examples.
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Creates specialized AI agents with optimized system prompts using the official 4-phase SOP methodology from Desktop .claude-flow, combined with evidence-based prompting techniques and Claude Agent SDK implementation. Use this skill when creating production-ready agents for specific domains, workflows, or tasks requiring consistent high-quality performance with deeply embedded domain knowledge.
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"Apply real options analysis to value managerial flexibility embedded in investment decisions. Use this skill when the user needs to evaluate projects with significant uncertainty and flexibility, assess the value of deferring or expanding investments, compare traditional NPV with expanded NPV, or when they ask 'should we wait to invest', 'what is the option to abandon worth', or 'why does NPV undervalue this project'.".
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"Apply case study research design (Yin) to investigate how and why questions within real-life contexts using single or multiple case designs and triangulation. Use this skill when the user needs to choose between single and multiple case designs, apply holistic versus embedded units of analysis, triangulate evidence from multiple sources, or when they ask 'how should I structure a case study', 'single or multiple cases', or 'how do I ensure validity in case research'.".
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Edge-hosted SQLite database with libSQL driver and embedded replicas
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Server-Side Template Injection (SSTI) occurs when user input is embedded directly into a template engine (Jinja2, Twig, Freemarker, Pebble, Velocity, Smarty, Mako) and evaluated, enabling remote code execution. Detect via math expressions `{{7*7}}` returning `49`, or `${7*7}`, `<%= 7*7 %>`. Leads to full RCE via template sandbox escape, Python `__class__.__mro__` traversal, and Java reflection chains. Tools: tplmap, Burp Suite.
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Perform static reverse engineering and analysis on Windows Portable Executable (PE) files to identify malicious indicators without executing the file. Use this skill during Incident Response, malware triage, or threat hunting to safely extract metadata, imported APIs, exported functions, embedded strings, and packed indicators from suspicious Windows binaries (.exe, .dll, .sys).
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Execute advanced LLM Jailbreaking techniques using roleplay, nested environments (virtual machines), and complex personas to completely bypass safety constraints and ethical alignments embedded in AI models.
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Identify and exploit default or weak credentials on web application login forms, admin panels, CMS backends (WordPress wp-admin, Joomla, Drupal), and embedded device management interfaces. Signals include framework fingerprinting (WhatWeb, Wappalyzer, Nikto), exposed admin paths from robots.txt/dirbusting, and weak password policy acceptance of "Password1" or "123456". Tools: Burp Suite Intruder, Hydra, Medusa, OWASP ZAP.
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Identifies cryptographic algorithms embedded in a binary by scanning for well-known constants and tables (AES S-box, SHA-256/MD5 init constants, ChaCha sigma, CRC32 table, base64 alphabet). Activates for requests to identify crypto in a binary, find AES/SHA constants, or detect which encryption algorithm a sample uses.
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Extracts structure and indicators from a Windows PE file without executing it: headers, sections, imports/exports, resources, entropy, and embedded strings to infer capability and packing. Activates for requests to statically analyze a PE, EXE, or DLL, or inspect imports and headers.
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Extracts an embedded malware configuration (C2 hosts, ports, campaign IDs, keys) from a process memory dump by locating decrypted config structures and decoding common obfuscation layers. Activates for requests to extract malware config from a memory dump, recover C2 settings from a running sample, or decode an in-memory configuration block.
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Analyzes Rust-compiled malware by detecting the Rust toolchain signature, demangling Rust v0/legacy symbol names, and identifying crate dependencies from embedded paths. Activates for requests to analyze Rust malware, demangle Rust symbols, or identify a Rust binary build and its crates.
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Analyzes weaponized Windows shortcut (.lnk) files: parsing the shell link structure for the target command, arguments, icon, and working directory, and recovering hidden PowerShell/cmd payloads and embedded content used in phishing. Activates for requests to analyze a malicious LNK, parse a shortcut file, or extract a command from a .lnk.
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Analyzes loader and dropper samples by identifying staging behavior — embedded or downloaded next-stage payloads, decode/decrypt routines, and the execution mechanism used to run the next stage. Activates for requests to analyze a loader or dropper, find a staged payload, or map multi-stage delivery behavior.
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Analyzes Go-compiled malware by recovering function names from the pclntab, detecting the Go build/version string, and listing embedded package paths to overcome stripped symbols. Activates for requests to analyze Go malware, recover Go function names, or identify a Golang binary build.
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Statically analyzes Linux ELF malware: ELF header and sections, dynamic symbols and imports, segment permissions, embedded strings, and packing indicators to infer capability without execution. Activates for requests to analyze an ELF binary, Linux malware, or shared object.
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Analyzes Python-based malware packaged as PyInstaller/py2exe executables by detecting the packer, locating the embedded archive, and identifying bundled .pyc modules for extraction and decompilation. Activates for requests to analyze compiled Python malware, unpack a PyInstaller binary, or extract pyc modules from a frozen Python executable.
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