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Found 523 Skills
Router skill for LLMQuant market-intelligence workflows. Use when the user needs macro views, market sentiment dashboards, or event probability signals.
Tracks how competitors position themselves online — scrapes homepages, features, pricing, and blogs to extract messaging, value props, CTAs, and pricing models. Compares against previous snapshots to surface positioning shifts with before/after tracking. Produces messaging matrices, content gap analysis, white space maps, and battlecard inputs. Use when anyone asks about competitor messaging, positioning, website copy, content strategy, or how competitors present themselves. Triggers: "competitor positioning", "messaging comparison", "content gap", "what changed on their site", "competitor homepage", "landing page teardown", "marketing battlecard", "how do they describe their product", "share of voice", "counter-messaging". Do NOT use for business signals like funding/hiring (use competitor-intel), single-company deep dives (use company-deep-dive), or meeting prep (use meeting-prep).
Search for job postings across LinkedIn and Indeed. Use when users want to find open roles, monitor hiring signals, identify companies hiring for specific positions, or research competitor hiring activity. Returns job title, company, location, salary, description, seniority level, and direct apply URLs. No login or cookies required.
What are crypto funds and VCs holding right now? Cross-chain fund portfolios and net accumulation signals.
Seamless.AI platform help — Prospector, Buyer Intent, Job Changes, CRM Enrich, Pitch Intelligence, Engagement Hub (email, calling, social), AI Agents, Autopilot, Chrome extension, API. Use when asking 'how do I do X in Seamless.AI', configuring Seamless.AI settings, searching for contacts/companies, setting up Buyer Intent, using Pitch Intelligence, managing AI Agents, or using the Seamless.AI API. Do NOT use for building prospect lists (use /sales-prospect-list), enriching contacts across tools (use /sales-enrich), interpreting buying signals across tools (use /sales-intent), cadence strategy (use /sales-cadence), cross-platform deliverability (use /sales-deliverability), or sales content strategy (use /sales-content).
Helps engineering managers support direct report growth — produces a stage-by-stage model of engineering impact (Circles of Influence), a framework for non-linear career planning (Tarzan Method), diagnostic signals for stalled growth, conversation scripts for career talks, and a promotion readiness vs. timing distinction. Use when the user says "career growth," "promotion," "career path," "this person wants to grow," "career conversation," "what's next for this person," "career ladder," "IC vs manager track," "how do I help my report advance," "help someone grow," or "engineer wants a promotion." Do NOT use for formal written performance reviews or underperformance — use performance-reviews instead.
Use this skill for ANY task involving jj or jujutsu version control. ALWAYS trigger when the user mentions jj, jujutsu, revsets, change IDs, bookmarks, or oplog. Also trigger when the user wants to squash, split, or reorder commits in a stack, write a revset query, absorb fixup changes, undo or restore a previous operation, resolve conflicts after rebasing, recover from force-pushes, rewrite protected/immutable commits, view change evolution (evolog), or try parallel approaches. Trigger even if "jj" is not explicitly said — "changes" instead of "commits", "stack" instead of "branch", "absorb", "squash into the right commit", "undo my last operation", "conflict after rebase", or "compare approaches in parallel" are strong jj signals. This skill contains critical non-obvious rules (like always using -m flags) that prevent broken workflows.
Expert Godot 4 game developer specializing in GDScript, the node/scene system, signals, resources, and engine-native patterns. Provides deep knowledge of Godot's unique architecture, performance optimization, and best practices for building games from simple prototypes to production-ready releases. Use when "godot, gdscript, godot 4, godot engine, build a game with godot, godot scene, godot node, godot signal, godot resource, godot tilemap, godot physics, godot animation, godot ui, godot multiplayer, godot, gdscript, game-engine, game-development, 2d-games, 3d-games, open-source" mentioned.
Deep research skill — broad parallel web searches, multi-source validation, confidence tracking, cited Markdown report. Supports 11 research types: market (TAM/SAM, segments, pricing, trends), domain (industry structure, ecosystem, regulatory landscape), technical (architecture, tools, benchmarks), competitive (competitor teardown, positioning, win/loss), product (feature analysis, reviews, roadmap signals), academic (literature survey, citation networks, key authors), person/org (due diligence on a company or public figure), financial (funding rounds, valuation multiples, revenue signals), legal (IP, patents, litigation, compliance), trend (emerging signals, foresight, scenario mapping), community (ecosystem health, key voices, governance, fragmentation). Use when asked to: 'research <topic>', 'deep dive on X', 'analyze the landscape', 'competitive analysis', 'compare these options', 'who are the players in Z', 'literature review', 'background on Y', 'what papers exist on X', 'product teardown', 'technology evaluation', 'regulatory overview', 'funding landscape', 'what trends are emerging in X', 'patent landscape', 'community health', or any request requiring scanning many sources and producing a cited written analysis. Apply whenever the deliverable is a thorough, sourced report rather than a quick answer. Trigger even when phrased casually: 'look into X', 'what's the deal with Y', 'dig into Z', 'I need to understand the space', 'catch me up on X'.
Use when the user needs to inspect Google Cloud (GCP) logs, metrics, and monitoring signals via gcloud for incident triage, debugging, or operational analysis. Supports Cloud Logging queries, Cloud Monitoring time-series reads, and environment checks for a target project.
Discover genes associated with diseases and traits using GWAS data from the GWAS Catalog (500,000+ associations) and Open Targets Genetics (L2G predictions). Identifies genetic risk factors, prioritizes causal genes via locus-to-gene scoring, and assesses druggability. Use when asked to find genes associated with a disease or trait, discover genetic risk factors, translate GWAS signals to gene targets, or answer questions like "What genes are associated with type 2 diabetes?"
Generate comprehensive rollout plans with preflight checks, step-by-step deployment, verification signals, rollback procedures, and communication plans for infrastructure and application changes