Locate CBaseEntity_EmitSoundFilter_SoundName in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the local gamedata entry "CBaseEntity_EmitSoundFilter_SoundName" (symbol CBaseEntity_EmitSoundFilter_SoundName). The gamedata consumer stores a BYTE SIGNATURE for this entry - ALWAYS emit the func schema (func_sig), never vfunc fields. The function may be virtual; locating it via the owning class vtable (RTTI) is a fine strategy, but once found, read its head bytes and emit func_sig. Locate via cross-references, distinctive constants/strings, callers of related symbols, or vtable slots; verify by decompilation before committing. Trigger: CBaseEntity_EmitSoundFilter_SoundName, CBaseEntity_EmitSoundFilter_SoundName
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mrc4tt/CS2_VibeSignatures☆ 3Updated Oct 15, 2026
Review JavaScript loops and replace suitable ones with standard array and object methods. Make transformations, filtering, and aggregation easier to understand, with practical explanations and browser checks to confirm that changes preserve the intended behavior.
- Refactoring manual loops into array methods
- Clarifying data transformation, filtering, and aggregation
- Reviewing object transformations and deep copying
thedaviddias/Front-End-Checklist☆ 74.5KUpdated Oct 6, 2026
Create Gmail filters that automatically label, star, or categorize incoming messages. Check existing labels, create a label when needed, define a filter, and verify its settings to organize recurring email.
- Automatically label incoming receipts
- Keep mail from a specified sender out of the inbox
- Check existing labels and configured filters
googleworkspace/cli☆ 31.7KUpdated Oct 7, 2026
Build fuzzy search that filters candidates and sorts them by relevance. Use saved match scores, search across multiple object fields, adjust acceptance thresholds, and connect ranking results to TanStack Table filtering and sorting.
- Sort search results by relevance
- Search names and email addresses together
- Adjust which fuzzy matches are accepted
TanStack/table☆ 28.5KUpdated Oct 13, 2026
Build or review quality control workflows for single-cell and single-nucleus RNA sequencing data. Select filters from observed data, detect doublets, assign cell types, and create UMAP plots that summarize cell relationships, while recording analysis decisions and outputs.
- Choosing quality filters from dataset distributions
- Detecting doublets and checking ambient RNA
- Assigning cell types using references or marker genes
openai/plugins☆ 7.5KUpdated Oct 8, 2026
Collect Trustpilot reviews for a company domain, with filters for ratings, language, dates, and reply status. Get structured review text, reviewer details, and company responses across pages to support reputation research and customer service analysis.
- Collect low-rated reviews to study customer complaints
- Gather reviews for competitor reputation comparisons
- Collect company replies and their publication dates
browser-act/skills☆ 6.2KUpdated Aug 24, 2026
Collect product listings from Walmart category pages, including prices, ratings, availability, and seller details. Use filtered category URLs and browse multiple pages to gather structured data for product comparisons and category research.
- Collecting products from a filtered category
- Comparing prices and ratings within a category
- Checking availability and seller information
browser-act/skills☆ 6.2KUpdated Aug 24, 2026
Bandpass, lowpass, bandstop filter design — hairpin, coupled-line, combline, stub, SIW for frequency selection and harmonic rejection. TRIGGER: user asks to design, create, or analyze any RF filter (bandpass, lowpass, highpass, bandstop, hairpin, coupled-line, combline, stub, SIW). Invoke BEFORE writing code — filter class names differ from what you would guess. SKIP: EM simulation/S-parameter extraction of an existing filter (use matlab-analyze-em), general PCB layout assembly (use matlab-assemble-pcb-layout), material/stackup setup only (use matlab-manage-pcb-material), optimization sweeps (use matlab-optimize-pcb-design).
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matlab/matlab-agentic-toolkit☆ 1.2KUpdated Oct 14, 2026
低信息量过滤工具。读取结构化数据文件,对指定文本列同时校验字符总数与行数是否落在阈值区间内,输出过滤后的合规行。 当用户提到低信息量过滤、字符数筛选、短文本过滤、超长文本过滤、行数过滤、信息量阈值等需求时使用此skill。 即使用户没有明确说出"低信息量",只要任务涉及同时按字符数和行数两个维度过滤文本行,就应该使用此skill。 不负责按单词数过滤(用words_num_filter)、按token数过滤(用token_num_filter)、按最长单行长度过滤(用maximum_line_length_filter)或按平均行长度过滤(用average_line_length_filter)。与这些skill的关键区别在于:本skill同时校验字符总数与行数两个维度,且原生支持CSV/TSV/Excel多列输入、不依赖data_juicer。
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cas-bigdatalab/piflow☆ 541Updated Oct 17, 2026
Score and filter topics for X content creation using weighted criteria. Use when user wants to evaluate collected materials, filter topics by score, or mentions "filter topics", "score materials", "x-filter", "选题筛选". Applies 10-point scoring system with customizable weights.
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kangarooking/x-skills☆ 337Updated Feb 21, 2026
Nexscope Ozon product report search: filters Ozon products by multi-dimensional metrics including sales, revenue, sales/revenue growth rate, cart conversion rate, order conversion rate, price, rating, review count, QA count, variant count, page views, gross margin, return/cancellation rate, ad spend share, weight/volume, listing time, brand, seller, fulfillment method, and labels. Returns each product's SKU, title, price (RUB), sales, revenue, lost revenue, conversion rate, rating, reviews, brand, seller, fulfillment method, listing days/months, and complete product report fields. Use for Ozon product selection, competitor product analysis, best-seller mining, price/conversion band filtering. Trigger when the user mentions Ozon product report, Ozon product selection, Ozon product filtering, Ozon product analysis, Ozon best-selling products, Ozon competitor product analysis, Ozon product report, Ozon product screener, filter Ozon products by sales, Ozon best-seller mining, Nexscope Ozon product report. Also trigger when the intent is to filter Ozon products by multiple metrics and view product-level reports, even without explicitly mentioning Nexscope.
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nexscope-ai/nexscope-ecommerce-skills☆ 96Updated Oct 15, 2026
Advanced Amazon product search and filtering powered by Nexscope data, supporting multi-dimensional criteria including category, price, monthly sales, keywords, BSR rank, review count, rating, package dimensions, weight, fulfillment type, and more. Trigger when users mention Nexscope product selection, Amazon product search, advanced product selection, BSR filtering, sales rank filtering, keyword-based product discovery, category search, competitor screening, niche product discovery, historical rank filtering, or similar terms. Even if the user does not explicitly mention "Nexscope," trigger this skill whenever the request involves multi-criteria Amazon product search, sales-metric-based filtering, or advanced product selection beyond simple keyword search.
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nexscope-ai/nexscope-ecommerce-skills☆ 96Updated Oct 15, 2026
Use Nexscope data to search and filter Amazon products, supporting multi-dimensional criteria including price, monthly sales, BSR ranking, gross margin, ratings, fulfillment method, badges, seller origin, and more across multiple Amazon marketplaces. Trigger when the user mentions Amazon product selection research, product filtering, sales filtering, product discovery, BSR analysis, niche product discovery, competitor analysis, market opportunity assessment, product-level market size estimation, gross margin screening, Nexscope product selection, Amazon product selection, sales filtering, BSR analysis, profit screening, market analysis, product selection tool. Even if the user does not explicitly mention "Nexscope", if their need involves filtering and analyzing Amazon product-level data for product selection, this skill should also be triggered.
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nexscope-ai/nexscope-ecommerce-skills☆ 96Updated Oct 15, 2026
Nexscope Product Database multi-condition filtering. Filter Amazon products by category, price, sales volume, revenue, reviews, rating, weight, BSR rank, LQS, seller type, and more across 10 marketplaces. Trigger when users mention Amazon product selection, product database filtering, BSR rank filtering, category-based product discovery, high-rating low-competition products, FBA product search, Amazon product discovery, or similar terms. Even if the user does not explicitly mention "Nexscope" or "product database," trigger this skill whenever the request involves filtering Amazon products by multiple criteria or discovering potential products.
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nexscope-ai/nexscope-ecommerce-skills☆ 96Updated Oct 15, 2026
Multi-dimensional Amazon product search and filtering based on Nexscope data, covering 14 marketplaces, with support for historical monthly snapshot lookback. Trigger when the user mentions Nexscope product search, Amazon product filtering, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, historical snapshot review, product search, monthly sales/revenue, ABA keyword product discovery, price range filtering, new product discovery, multi-condition combined filtering, product search, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, historical snapshot. Even if the user does not explicitly mention "Nexscope", if their need involves Amazon product search, filtering, comparison, or product exploration by category/brand/seller dimensions, this skill should also be triggered.
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nexscope-ai/nexscope-ecommerce-skills☆ 96Updated Oct 15, 2026
Manipulate row selection (`df.selection`) on a Datagrok DataFrame via the datagrok_exec tool — set, clear, invert, add to, remove from, intersect, and read the selection mask. Also covers current row (`df.currentRowIdx`), the cross-skill bridges to/from the filter, and how to materialize the selected rows as a new DataFrame. Use whenever the user says "select rows", "deselect", "invert selection", "highlight rows", "selected rows", "clear selection", "current row", "currentRowIdx", "count selected", "list selected indexes", "selection from filter", "filter from selection", or asks for selected rows as a new table. Does NOT cover row filtering (separate skill `datagrok-filtering`) or generic DataFrame cloning (`datagrok-df-and-columns`).
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datagrok-ai/public☆ 74Updated Oct 20, 2026
Use when setting the default filtered set of records a user sees in list views, reports and SOQL without removing their access. Trigger keywords: scoping rule, Filter by scope, default record scope, RestrictionRule enforcementType Scoping, Object Manager scoping rule, recordFilter. NOT for the SOQL USING SCOPE clause - use apex/soql-using-scope-clause. NOT for blocking record access - use admin/restriction-rules.
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PranavNagrecha/AwesomeSalesforceSkills☆ 19Updated Oct 20, 2026
Customize WP Rocket behavior from a third-party plugin / theme via filter hooks — exclude URIs / cookies / user agents / REST API namespaces from caching, configure CDN URL rewrites, extend lazy load handling, override capability requirements, hook into Action Scheduler integration. Critical guidance — rocket_cache_reject_uri takes URI patterns (regex-like), NOT full URLs; rocket_cache_reject_* filters all expect arrays. The rocket_buffer filter is the FULL HTML output filter — extremely powerful but dangerous; one fatal error in the callback breaks every cached page until WP Rocket is disabled. Use when extending WP Rocket's default rules, NOT for cache invalidation (see wp-rocket-cache-invalidation). Triggers on rocket_cache_reject_, rocket_cdn_, do_rocket_lazyload, rocket_buffer, rocket_capacity, "exclude from WP Rocket cache".
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nvdigitalsolutions/mcp-ai-wpoos☆ 7Updated Oct 20, 2026
Mutate WooCommerce variation prices via filters — pick the right layer (woocommerce_product_get_price for simple/non-variation products, woocommerce_product_variation_get_price for variations, the woocommerce_variation_prices_* family for the parent min/max aggregation that feeds the catalog "From X to Y" range), and the critical step of filtering woocommerce_get_variation_prices_hash whenever your price logic depends on context outside the default cache key (user role, custom toggle, time of day) — otherwise one user's filtered price gets cached and served to everyone. Use for role-based pricing, time-based discounts, or "filter variation prices but the min/max range doesn't update" debugging. Triggers on woocommerce_product_get_price, woocommerce_product_variation_get_price, woocommerce_variation_prices_*, woocommerce_get_variation_prices_hash, wc_var_prices.
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nvdigitalsolutions/mcp-ai-wpoos☆ 7Updated Oct 20, 2026
Agent fallback for CBaseTrigger_PassesTriggerFilters (auto-generated, category: vfunc). Locate CBaseTrigger::PassesTriggerFilters in the CS2 server module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: CBaseTrigger_PassesTriggerFilters, CBaseTrigger::PassesTriggerFilters
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mrc4tt/CS2_VibeSignatures☆ 3Updated Oct 15, 2026
Agent fallback for CBaseFilter_InputTestActivator (auto-generated, category: func). Locate CBaseFilter::InputTestActivator in the CS2 server module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: CBaseFilter_InputTestActivator, CBaseFilter::InputTestActivator
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mrc4tt/CS2_VibeSignatures☆ 3Updated Oct 15, 2026
Agent fallback for CBaseEntity_EmitSoundFilter (auto-generated, category: func). Locate CBaseEntity::EmitSoundFilter in the CS2 server module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: CBaseEntity_EmitSoundFilter, CBaseEntity::EmitSoundFilter
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mrc4tt/CS2_VibeSignatures☆ 3Updated Oct 15, 2026
Review URL parameters used for filters, sorting, pagination, and tracking. Check canonical tags, which identify a preferred page URL, and recommend consistent handling of URL variants to address duplicate content and unnecessary search engine crawling.
- Reviewing filtered and sorted product URLs
- Removing tracking parameters from canonical URLs
- Investigating crawlable URL combinations
thedaviddias/Front-End-Checklist☆ 74.5KUpdated Oct 6, 2026
Screen compound libraries for drug discovery using drug-likeness guidelines, structural alerts that flag patterns for review, and molecular complexity measures. Combine criteria to shortlist candidates and retain filtering results with reasons for further assessment.
- Screen compound libraries with drug-likeness rules
- Flag PAINS and other structures for review
- Combine property, structure, and complexity filters
K-Dense-AI/scientific-agent-skills☆ 53.1KUpdated Oct 19, 2026