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The ORFhunteR package is a R and C++ library for an automatic determination and annotation of open reading frames (ORF) in a large set of RNA molecules. It efficiently implements the machine learning model based on vectorization of nucleotide sequences and the random forest classification algorithm. The ORFhunteR package consists of a set of functions written in the R language in conjunction with C++. The efficiency of the package was confirmed by the examples of the analysis of RNA molecules fr

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This is an R package for interfacing with the BIOM format. This package includes basic tools for reading biom-format files, accessing and subsetting data tables from a biom object (which is more complex than a single table), as well as limi

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mzR provides a unified API to the common file formats and parsers available for mass spectrometry data. It comes with a subset of the proteowizard library for mzXML, mzML and mzIdentML. The netCDF reading code has previously been used in XC

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Expert knowledge for Azure Firmware Analysis development including best practices, security, integrations & coding patterns, and deployment. Use when configuring RBAC/service principals, uploading firmware via CLI/PowerShell/Python, mapping results to Device Registry, reading SBOM paths, or deploying workspaces with ARM/Bicep/Terraform, and other Azure Firmware Analysis related development tasks. Not for Azure Defender For Iot (use azure-defender-for-iot), Azure IoT Edge (use azure-iot-edge), Azure IoT Hub (use azure-iot-hub), Azure Confidential Computing (use azure-confidential-computing).

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Use ONLY when calling the `browser_execute` tool or driving a real browser via the Chrome DevTools Protocol. Required reading before the first `browser_execute` call in a session. Covers the three connection methods (local Chrome with remote debugging, isolated debug-port profile, Browser Use cloud), the in-process `session` / `console` snippet model, attaching to a page target, common CDP commands, the per-project `.bcode/agent-workspace/` for reusable scripts, and screenshot auto-attachment.

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Provides guidance for writing, optimizing, and benchmarking C++ CPU kernels with SIMD intrinsics (AVX2/AVX512) for the Hugging Face kernels ecosystem. Includes a two-phase workflow: Phase 1 correctness (generic → AVX2) and Phase 2 performance exploration (AVX512 with branching trial loop), runtime CPU dispatch, OpenMP threading, and brgemm integration for GEMM-heavy kernels.

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Initializes an AI development session by reading workflow guides, developer identity, git status, active tasks, and project guidelines from .trellis/. Classifies incoming tasks and routes to brainstorm, direct edit, or task workflow. Use when beginning a new coding session, resuming work, starting a new task, or re-establishing project context.

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Use before claiming work is complete, fixed, or passing — before committing, opening a PR, or handing off. Requires running the verification command in THIS turn and reading its output before any success claim.

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Run the fixed 6-step session-opening sequence — pwd, read progress, git log, count remaining features, init.sh, smoke-test last feature — before touching any new work. The orientation ritual that lets fresh-context sessions reconstruct project state in under a minute.

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IATA cabin codes (F/J/W/Y) and saver fare class codes (X/I/O) for reading award inventory and determining partner-bookable availability.

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Guides the generation, reading, and updating of agentmap.md files. This skill ensures a consistent and up-to-date codebase map for AI Agents.

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Any live-web task via the Firecrawl CLI — including ordinary web research: searching the web, reading or extracting pages, gathering sources, discovering site URLs, bulk extraction, downloading a site, change alerts, or pages needing clicks/login — web only; local files route to firecrawl-parse. For US legal or regulatory questions use gov; for papers use firecrawl-research-index; for library, API, error, or bug questions use firecrawl-developer-index.

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Use when syncing real-time data, structuring JSON trees, reading/writing, creating listeners, enabling offline persistence, managing presence, sharding, or writing security rules.

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Acceptance test creation methodology for the DISTILL wave. Domain knowledge for the acceptance designer agent: port-to-port principle, prior wave reading, wave-decision reconciliation, graceful degradation, and document back-propagation.

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How the nWave buddy agent reads a project to answer questions — detection, order of inspection, and citation discipline.

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Monthly, and on its first run it is the whole setup, launched by hand. It discovers what the member actually runs by walking their code roots and reading the registrar, the host, and the hosted database, then writes the inventory, the domains file, the starting budgets, and the opening safe fix rules, seeds the board, builds the dashboard, and registers one scheduled job per routine. It creates no account, buys nothing, and provisions nothing.

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Weekdays, file work only, no browser at all. Reads every ledger and run record since its cursor, resolves which drafted changes actually merged by reading the commit graph rather than a dashboard, closes and reopens incidents on that evidence, folds the card inbox, re-renders the review board, and writes the short morning brief the member opens first. It never merges, never deploys, and never touches a credential.

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Weekdays. Produces one creative set per run against evidence rather than taste, reading the standing doctrine for the angles currently earning and the metrics ledger for what has decayed. It writes the images and the exact strings into a dated local set folder with the destination screen named, files one card, and uploads nothing to any account. It never opens an account screen, sends only where you released the channel, spends only where you released it, and never touches a credential.

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Weekly, browser heavy, read only on every screen. Fixes a scoring window that neither double counts nor loses an hour, reads the member's search performance console and analytics property, verifies each range actually applied before reading a figure, reconciles every number against what this Employee published, writes the week's scoreboard and the short rolling state file every other routine reads, and files what it found as cards rather than doing the work itself. It types nothing on any screen, changes no setting, publishes nothing, and never touches a credential.

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Weekly. Audits the paid and measurement setup the member already has by reading it, then assembles the parts that are missing as local files: campaign structure, ad copy, negative keyword seeds, and conversion tracking specifications, each one complete and ready to paste. It creates nothing in an account, saves nothing, activates nothing, and spends nothing, unless you released the channel. This is where the spend stop lives.

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Use when a brand faces a communications CRISIS or a campaign is failing in public — L1 to L5 severity classification, a first-four-hours process, response templates by type, an escalation matrix, a do-not-do list, holding statements, and a post-mortem. Trigger on 'PR crisis', 'crisis playbook', 'a complaint is going viral', 'bad reviews are spreading', 'our content caused backlash', 'we are getting attacked online'. Also use when the user forwards an angry thread and asks what to do right now. Not for — monitoring before anything blows up, see `15-social-listening-global`; diagnosing weak performance numbers, see `03-performance-eval-global`; the routine post-campaign review, see `63-campaign-retrospective-global`.

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Use when the user wants to monitor what is being said about the brand, competitors, and the category — channels and keywords to track, sentiment scoring, weekly and monthly listening reports, brand health metrics, early crisis detection, and content opportunities pulled from real conversations. Trigger on 'social listening', 'brand monitoring', 'sentiment analysis', 'what are people saying about us', 'track our mentions', 'monitor competitors online'. Also use when the user spotted a bad comment thread and wants to know if it is spreading. Not for — responding to a crisis already underway, see `66-crisis-playbook-global`; competitor strategy teardown, see `08-competitor-research-global`; auditing your own posts, see `39-content-audit-global`.

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Automatically organizes invoices and receipts for tax preparation by reading messy files, extracting key information, renaming them consistently, and sorting them into logical folders. Turns hours of manual bookkeeping into minutes of automated organization.

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Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.

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