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Found 556 Skills
Guides QA engineers through daily testing activities—morning review, test case creation, automation, exploratory testing, bug reporting, and end-of-day wrap-up. Use when planning or executing day-to-day testing or when the user asks about daily testing workflow.
Design exploration with parallel agents. Use when brainstorming ideas, exploring solutions, or comparing alternatives.
Explore-lane experimental execution skill for deep learning research repositories. Use when the researcher explicitly authorizes exploratory runs such as small-subset validation, short-cycle guess-and-check, batch sweeps, idle-GPU search, or quick transfer-learning trials, with results summarized in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline execution, conservative training verification, default routing, or implicit experimentation.
Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.
Meta-skill for internal codebase exploration at varying depths (quick/deep/architecture)
Teaches learners to extract transferable design lessons from real-world codebases through critical evaluation and systematic exploration. Use when a learner wants to study existing code to learn patterns, architecture, or design decisions—not just understand what it does. Guides through navigation, pattern recognition, critical evaluation (deliberate choice vs. compromise), and lesson extraction. Triggers on phrases like "learn from this codebase", "study how X is implemented", "understand design patterns in Y", or when a learner wants to improve by reading real code.
Socratic discovery and design exploration before planning. Activates when starting non-trivial work — asks clarifying questions, explores alternatives and tradeoffs, produces a design document for approval. Pulls context from Linear issue description, linked docs, and existing CLAUDE.md learnings. Simple bugs and fixes skip this automatically.
Documents the results of a time-boxed technical or design exploration (spike). Use after completing a spike to capture learnings, findings, and recommendations for the team.
Plan, draft, audit, and publish LinkedIn posts and comments. Use when the user wants to write a viral LinkedIn post, draft a comment or reply on any LinkedIn post URL, audit a draft against 2026 algorithm heuristics, remove AI tells, extract hook formulas from viral posts, or plan a week of content. Powered by the Publora API for publishing. User provides post/comment URLs, skill drafts content, user approves, then publishes.
Fine-tune vision-language models (VLMs) with supervised learning on image+text data. Use when adapting a VLM to a visual domain or task, configuring frozen-vision-tower LoRA, or debugging a VLM fine-tune that trains without learning.
Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to dogfood, QA, exploratory test, find issues, bug hunt, or test this app on mobile.
Judges whether RHDH Jira work that already exists is ready to move forward — in RHIDP, RHDHPLAN, RHDHBUGS, and RHDHSUPP. Checks an issue, a JQL result, a sprint, or a backlog against the exit criteria for its status, then reports missing fields, hierarchy gaps, likely duplicates, unaddressed comments, stale work, and Feature Exploration readiness. Use for "is RHIDP-1234 ready", "refine this", "refine the backlog", "backlog hygiene", "what's missing on this epic", "run the Feature Exploration checklist", or "which of these are stale". Assesses existing work; it does not open new issues and does not build a sprint.