Loading...
Loading...
Found 1,115 Skills
Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects.
Analyze MSBuild binary logs to diagnose build failures by replaying binlogs to searchable text logs. Only activate in MSBuild/.NET build context. USE FOR: build errors that are unclear from console output, diagnosing cascading failures across multi-project builds, tracing MSBuild target execution order, investigating common errors like CS0246 (type not found), MSB4019 (imported project not found), NU1605 (package downgrade), MSB3277 (version conflicts), and ResolveProjectReferences failures. Requires an existing .binlog file. DO NOT USE FOR: generating binlogs (use binlog-generation), build performance analysis (use build-perf-diagnostics), non-MSBuild build systems. INVOKES: dotnet msbuild binlog replay, grep, cat, head, tail for log analysis.
Expert assistant for BuilderBot (v1.4.0) — a TypeScript/JavaScript framework for building multi-platform chatbots (WhatsApp, Telegram, Instagram, Email, etc.). Use when creating or editing flows (addKeyword, addAnswer, addAction), wiring EVENTS, managing per-user state or globalState, configuring providers (Baileys, Meta, Telegram, Evolution, etc.) or databases (Mongo, Postgres, MySQL, JSON), implementing REST API endpoints (handleCtx, httpServer), debugging flow control (gotoFlow, endFlow, fallBack, idle, capture, flowDynamic), or handling blacklist logic. Architecture: Provider + Database + Flow.
Integrate Polpo AI agents into any TypeScript/JavaScript application using @polpo-ai/sdk. Use when the user wants to add AI agent chat, completions API, streaming SSE, session management, memory, webhooks, or any Polpo API integration into their code. Triggers on "polpo", "agent chat", "completions API", "polpo sdk", "@polpo-ai/sdk", "AI agent integration".
Structural validation and damage systems for Three.js building games. Use when implementing building stability (Fortnite/Rust/Valheim style), damage propagation, cascading collapse, or realistic physics simulation. Supports arcade, heuristic, and realistic physics modes.
Authoritative reference for Odoo 19 syntax conventions across Python ORM, XML views, OWL/JavaScript, controllers, manifests, and SCSS. Use this skill BEFORE writing or modifying any Odoo code, whenever the user mentions Odoo, an Odoo module, an Odoo model, an XML view, an OWL component, or any file under an Odoo addons directory. Odoo 19 introduces breaking changes (130 model renames, res.groups privilege refactor, hr.contract→hr.version, models.Constraint, attrs removal continued, type='jsonrpc') that older training data does NOT reflect. Always consult this skill before generating code, even if the request looks routine — a model that "obviously" works in Odoo 18 may be wrong in Odoo 19. Trigger this skill on phrases like "create an Odoo module", "add a field to res.partner", "write a controller", "make an OWL component", "fix this Odoo view", "_sql_constraints", "tree view", or any time you see a `__manifest__.py`, `models/*.py`, `views/*.xml`, or `static/src/**/*.js` file in an Odoo project.
Enforce C++ coding standards including camelCase or snake_case variables, PascalCase classes, and consistent file naming.
Use when a Head of People Ops, BizOps lead, or Internal Communications owner needs to draft and sequence an internal-only change-management communication — a re-org announcement, a tool rollout, a policy change, a benefit change, a leadership transition, a layoff, an acquisition close, or an internal product launch — and the audience is employees (not customers). Triggers on "all-hands announcement", "town-hall script", "change comms", "internal newsletter", "rollout comms", "policy change announcement", "re-org announcement", "internal FAQ", "manager talking points", "Prosci ADKAR", "Kotter 8-step", "layoff comms", "RIF comms", "internal memo". Pairs Prosci ADKAR (Awareness / Desire / Knowledge / Ability / Reinforcement) and Kotter's 8-step change model with deterministic stdlib-only Python tools to produce a sequenced touchpoint calendar, a Kotter-compliant primary announcement, an audience-segmented FAQ, and manager cascade talking points. Industry-tuned via --profile {tech-startup, scaleup, enterprise, public-company, non-profit}. Distinct from marketing-skill/* (external/customer-facing), c-level-advisor/internal-narrative (strategic framing, not tactical drafts), and c-level-advisor/change-management (executive change strategy, not the comms package itself).
Decision frameworks for DatoCMS content modeling — schema shape, field choice, content reuse, taxonomies, content vs presentation, admin UI organization. Use for modeling *decisions*, not implementation: model vs block; single_block vs Modular Content vs Structured Text; references vs embedded blocks; taxonomy shape (flat/tree/faceted); refactoring page-shaped schemas to reusable content; fitting 300 KB / 500-block / 5-level record limits; model behaviour (singleton, draft mode, all_locales_required, sortable/tree/ordering_field, presentation_title_field, collection_appearance, inverse_relationships_enabled); field config (validator + appearance — enum + string_select, slug auto-fill, required_alt_title, structured_text allowlists, framed vs frameless single_block). Also schema review (reuse, editor ergonomics, omnichannel). *Creating* schema → `datocms-cli` or `datocms-cma`. Query/render → `datocms-cda` + `datocms-frontend-integrations`. Validators + cascade: `datocms-cma/references/schema.md`.
Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), vector and raster data operations, spatial statistics, point cloud processing, network analysis, cloud-native workflows (STAC, COG, Planetary Computer), and 8 programming languages (Python, R, Julia, JavaScript, C++, Java, Go, Rust) with 500+ code examples. Use for remote sensing workflows, GIS analysis, spatial ML, Earth observation data processing, terrain analysis, hydrological modeling, marine spatial analysis, atmospheric science, and any geospatial computation task.
Use after story and spec synthesis to perform a strict delivery handoff review, identify remaining gaps or contradictions, and score readiness for engineering and cross-functional execution. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution. Explicit full or end-to-end spec refinement requests continue through the existing 18-stage refinement cascade.
Use after PRFAQ and BRD creation to run a strict final quality review, identify gaps or contradictions, and assign a readiness score before design or development starts. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution. Explicit full or end-to-end spec refinement requests continue through the existing 18-stage refinement cascade.