Results for “spl”

Find and identify the CCSPlayerPawn_SnapEyeAngles function in CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the non-virtual SnapEyeAngles method. It is the one caller of the shared apply helper (CCSPlayerPawn_ApplyEyeAngleNetworkChange) that is NOT CCSPlayerPawn_SnapViewAngles. Emits a unique IDA-style byte signature and a func YAML. Mirrors the find-CCSPlayerPawn_SnapEyeAngles.py preprocessor (xref_funcs apply-helper, exclude_funcs SnapViewAngles). Trigger: CCSPlayerPawn_SnapEyeAngles, SnapEyeAngles

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Locate CCSPlayerPawn::SetEyeAngles in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the local gamedata entry "CCSPlayerPawn::SetEyeAngles" (symbol CCSPlayerPawn_SetEyeAngles). This is a non-virtual function - emit a byte signature (func_sig), not an offset. Locate it via cross-references, distinctive constants/strings in its body, or callers of related symbols; verify by decompilation before committing to a candidate. Trigger: CCSPlayerPawn_SetEyeAngles, CCSPlayerPawn::SetEyeAngles

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Locate CCSPlayerInventory::SendInventoryUpdateEvent in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the WeaponPaints gamedata entry "CCSPlayerInventory::SendInventoryUpdateEvent" (symbol CCSPlayerInventory_SendInventoryUpdateEvent). Shortlist via functions constructing the inventory-full-update usermessage/event around m_pSOCache contents for the owning controller. The body packs the SO cache snapshot and sends it via the GC/usermessage path. Cross-check with callers in inventory-dirty flows (weapon paint mutations). Trigger: CCSPlayerInventory_SendInventoryUpdateEvent, CCSPlayerInventory::SendInventoryUpdateEvent

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Locate CCSPlayerController::HandleCommand_JoinTeam in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the local gamedata entry "CCSPlayerController::HandleCommand_JoinTeam" (symbol CCSPlayerController_HandleCommand_JoinTeam). This is a non-virtual function - emit a byte signature (func_sig), not an offset. Locate it via cross-references, distinctive constants/strings in its body, or callers of related symbols; verify by decompilation before committing to a candidate. Trigger: CCSPlayerController_HandleCommand_JoinTeam, CCSPlayerController::HandleCommand_JoinTeam

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Locate CCSPlayer_WeaponServices::GetSlot in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the local gamedata entry "CCSPlayer_WeaponServices::GetSlot" (symbol CCSPlayer_WeaponServices_Weapon_GetSlot). This is a non-virtual function - emit a byte signature (func_sig), not an offset. Locate it via cross-references, distinctive constants/strings in its body, or callers of related symbols; verify by decompilation before committing to a candidate. Trigger: CCSPlayer_WeaponServices_Weapon_GetSlot, CCSPlayer_WeaponServices::GetSlot

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Build effective detection rules using Splunk Search Processing Language (SPL) correlation searches to identify security threats in SOC environments.

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Analyze AWS IAM access policies with boto3 and Cloudsplaining-style checks to find permissions that could grant greater access. Produces a JSON report linking risky permissions to users or roles, with severity ratings and remediation guidance.

• Audit AWS IAM policies for excessive permissions
• Find permission combinations that enable privilege escalation
• Trace risky policies to affected users and roles

Investigate Active Directory authentication logs with Splunk and KQL queries to find signs of Golden Ticket attacks, which use forged Kerberos authentication tickets. Examine encryption mismatches, missing ticket requests, unusual lifetimes, and account inconsistencies.

• Hunting for forged tickets after credential theft
• Investigating encryption mismatches in authentication logs
• Checking for persistent access after incident response

Create interactive 3D scenes for websites, including product views and scroll-driven animations. Covers choosing Three.js, React Three Fiber, or Spline, preparing lightweight models, showing loading progress, and adapting experiences for mobile devices.

• Building an interactive 3D product configurator
• Adding 3D scenes to a portfolio
• Animating models and cameras as visitors scroll

Build, run, and debug the Kilo JetBrains plugin using its Gradle workflows. It covers isolated development storage, chat logs, sandbox recovery, and switching between a pinned CLI release and locally built CLI code.

• Build a versioned plugin ZIP for testing
• Run the plugin in a sandbox or split mode
• Inspect chat logs and session events

Arrange tabs and split panes in the Superset desktop app so terminals, tests, and logs appear where needed. Open panes with commands, resize or move them, switch focus, and close extra panes while optionally keeping their terminals running.

• Showing the server and tests side by side
• Opening logs in a new tab
• Resizing and equalizing split panes

Split a large commit or branch into a Graphite PR stack, a series of dependent review requests. Group changes by purpose, preserve changes that must stay together, and verify that each lower layer builds and passes tests independently.

• Splitting a large PR by the decisions reviewers need to assess
• Checking whether a refactor can be separated safely
• Verifying that a lower PR builds and passes tests on its own

Make 3D canvas output sharper on Retina and other high-density displays. Coordinate rendering and post-processing resolution, preserve pointer accuracy, and verify fixed 200% rendering or automatic scaling with measured performance and explicit fallbacks.

• Fix blurry 3D canvas output on Retina displays
• Implement a fixed 200% rendering option
• Keep post-processing and pointer coordinates aligned

Detects aberrant splicing in single rare-disease patients vs a control panel using FRASER 2.0 (Bioconductor; Beta-binomial autoencoder on Intron Jaccard Index, default delta cutoff 0.1, q hyperparameter), OUTRIDER (gene-level outlier expression via autoencoder denoising), LeafcutterMD (Dirichlet-multinomial outlier mode of LeafCutter for annotation-free junctions), and DROP (Snakemake pipeline integrating FRASER2 + OUTRIDER + monoallelic expression for clinical diagnostics). The statistical model is fundamentally different from differential splicing — single-sample-vs-cohort outlier detection rather than two-group comparison. Standard tool in EU rare-disease (Solve-RD) and NIH UDN programs. Use when applying RNA-seq to undiagnosed Mendelian disease, validating predicted splice variants in clinical samples, or detecting cryptic splicing in disease tissue.

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Analyzes alternative splicing at single-cell resolution. The first decision is library chemistry — 10X 3' is fundamentally limited (RT primes from poly-A, R2 falls in 3' UTR, <0.1 junction read per cell per AS event). Plate-based full-length methods (Smart-seq3, FLASH-seq, VASA-seq, STORM-seq) and single-cell long-read (MAS-Iso-seq, scISOr-Seq2) are the chemistries that give per-cell isoform structure. Tools include MARVEL (R, Smart-seq integrated), BRIE2 (Bayesian PSI with regulatory features and ELBO_gain test), scQuint (junction-cluster, plate-based; not for 10X), SpliZ (annotation-free Z-score), Psix (graph-smoothness regulated AS), and Sierra (alternative polyadenylation, often confused with AS). Use when analyzing isoform usage in scRNA-seq, identifying cell-type-specific splicing, or determining whether scRNA-seq chemistry supports splicing analysis at all.

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When the user wants to run display, banner, or ad network campaigns. Also use when the user mentions "display ads," "banner ads," "ad network," "ad alliance," "programmatic display," "native ads," or "retargeting display." For strategy, use paid-ads-strategy.

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The analysis and visualization of alternative splicing (AS) events from RNA sequencing data remains challenging. SpliceWiz is a user-friendly and performance-optimized R package for AS analysis, by processing alignment BAM files to quantify read counts across splice junctions, IRFinder-based intron retention quantitation, and supports novel splicing event identification. We introduce a novel visualization for AS using normalized coverage, thereby allowing visualization of differential AS across

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Execute an approved split plan, shipping each change group separately as its own branch and PR or as sequential commits on the current branch. Use when the user asks to "split and ship", "ship the split plan", "create separate PRs", or "split changes into branches".

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Publishes HTML or Markdown as display.dev URLs with public, company, or private access. Supports signup, claiming, sharing, browsing, bounded reads, exact edits, and comment iteration. Use when the user asks to "publish this", "share this", "share with the org", "post this online", "make a private link", "share with [email]", "publish a report", "list my artifacts", "find an artifact", "publish a large file", "publish this generated HTML file", "read this artifact", "search inside this artifact", "change this passage", "make a copy of this artifact", "duplicate version", "create a display.dev account", "claim this publish", "add a company email domain", "transfer an email domain", "change the email domains add-on", "watch comments on this artifact", "respond to comments", or "resolve this comment thread". Use whenever a request contains a display.dev artifact URL (`*.dsp.so/*`). Anonymous publishing returns a 30-day preview and browser claim URL.

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Split user stories into smaller, independently deliverable slices using the SPIDR method (Spike, Path, Interface, Data, Rules). Use this skill whenever the user asks to split a story, break down work, slice a story, asks "can this be split", mentions "SPIDR", says "story splitting", or wants to decompose a large ticket into smaller pieces. Also trigger when a user presents a story that seems too large for a single sprint and asks for help sizing or scoping it.

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Configures the rollout shape of a PostHog experiment — the variant split (50/50, 80/20, A/B/C ratios), the overall rollout percentage that gates how many users enter the experiment, and the disambiguation when a percentage like "roll out to 25%" could mean either. Use when the user mentions a rollout percentage, variant split, or traffic distribution; gives a ratio like 60/40, 70/30, or 80/20; asks "who sees the test variant?"; wants to increase, decrease, or change the rollout or split on a draft or running experiment; weighs equal vs uneven splits; or proposes a mid-experiment split change (often an anti-pattern that needs reset or end-and-restart).

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Analyzes alternative splicing at single-cell resolution. The first decision is library chemistry — 10X 3' is fundamentally limited (RT primes from poly-A, R2 falls in 3' UTR, <0.1 junction read per cell per AS event). Plate-based full-length methods (Smart-seq3, FLASH-seq, VASA-seq, STORM-seq) and single-cell long-read (MAS-Iso-seq, scISOr-Seq2) are the chemistries that give per-cell isoform structure. Tools include MARVEL (R, Smart-seq integrated), BRIE2 (Bayesian PSI with regulatory features and ELBO_gain test), scQuint (junction-cluster, plate-based; not for 10X), SpliZ (annotation-free Z-score), Psix (graph-smoothness regulated AS), and Sierra (alternative polyadenylation, often confused with AS). Use when analyzing isoform usage in scRNA-seq, identifying cell-type-specific splicing, or determining whether scRNA-seq chemistry supports splicing analysis at all.

The English summary is being prepared. Showing the original description.

Detects aberrant splicing in single rare-disease patients vs a control panel using FRASER 2.0 (Bioconductor; Beta-binomial autoencoder on Intron Jaccard Index, default delta cutoff 0.1, q hyperparameter), OUTRIDER (gene-level outlier expression via autoencoder denoising), LeafcutterMD (Dirichlet-multinomial outlier mode of LeafCutter for annotation-free junctions), and DROP (Snakemake pipeline integrating FRASER2 + OUTRIDER + monoallelic expression for clinical diagnostics). The statistical model is fundamentally different from differential splicing — single-sample-vs-cohort outlier detection rather than two-group comparison. Standard tool in EU rare-disease (Solve-RD) and NIH UDN programs. Use when applying RNA-seq to undiagnosed Mendelian disease, validating predicted splice variants in clinical samples, or detecting cryptic splicing in disease tissue.

The English summary is being prepared. Showing the original description.

Detects aberrant splicing in single rare-disease patients vs a control panel using FRASER 2.0 (Bioconductor; Beta-binomial autoencoder on Intron Jaccard Index, default delta cutoff 0.1, q hyperparameter), OUTRIDER (gene-level outlier expression via autoencoder denoising), LeafcutterMD (Dirichlet-multinomial outlier mode of LeafCutter for annotation-free junctions), and DROP (Snakemake pipeline integrating FRASER2 + OUTRIDER + monoallelic expression for clinical diagnostics). The statistical model is fundamentally different from differential splicing — single-sample-vs-cohort outlier detection rather than two-group comparison. Standard tool in EU rare-disease (Solve-RD) and NIH UDN programs. Use when applying RNA-seq to undiagnosed Mendelian disease, validating predicted splice variants in clinical samples, or detecting cryptic splicing in disease tissue.

The English summary is being prepared. Showing the original description.