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Create and run automated tests that score LLM answers against expected outputs or judging criteria. Monitor progress, inspect individual results, compare models on the same tests, and use score thresholds in CI, an automated checking workflow.
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Track objectives across multiple conversations by defining milestones, saving progress and findings, and planning each session. Review completion criteria and flag schedule risks, scope changes, or dependencies that may require a different approach.
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Run one cycle of autonomous task work in Claude Code: check progress, select and execute the next action, log the work, and schedule another cycle. Stop when all tasks are complete or the iteration limit is reached.
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Choose the next task using patterns learned from completed work and current progress. The skill acts on confident predictions, falls back to task priorities when confidence is low, and updates its learning after completion.
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Review website JPEGs for progressive encoding, which displays a blurry preview before sharpening. Identify images that could use this format, consider file size and loading behavior together, and explain how to confirm the change in browser developer tools.
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Learn AI engineering by building a project one stage at a time. The tutor guides predictions, learner-written code, automated checks, and reflection, then records progress so the next session can continue from the right stage.
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Study AI engineering through interactive terminal lessons with explanations, coding exercises, and quizzes. The tutor follows your recorded progress, revisits previous material, adapts to your answers, and logs results and topics that need review.
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Plan and track work in Asana by assigning task owners, updating deadlines and status, and setting dependencies between tasks. Review project progress, comments, teams, and workspaces through Asana's official connection for AI tools.
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Build asset loading for Three.js scenes, including 3D models, textures, and HDR images for backgrounds and reflections. Coordinate multiple files, track loading progress, reuse cached assets, and handle failures with retries or fallback files.
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Plan protein characterization experiments with Adaptyv's cloud laboratory, estimate costs, submit sequences, track progress, and retrieve measured results. Supports binding, thermal stability, expression, fluorescence, and enzyme activity workflows through the API and Python SDK.
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Build and modify Java plugins for Minecraft servers running Paper, Spigot, or Bukkit. The skill covers commands, event handling, minigames, and saved player progress, with checks for configuration, task cleanup, and server API compatibility.
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Help junior developers and AI newcomers understand code through guided questions and progressive hints. Support debugging, concept learning, and critical review of AI-generated code so learners can explain their reasoning and work toward solutions themselves.
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Break a development task into small requirements with explicit acceptance criteria, then repeat implementation and verification while saving progress. Completion depends on evidence for each requirement and reviewer approval, with configurable reviewers and a final cleanup check.
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Map intrusion evidence to the seven stages of the Lockheed Martin Cyber Kill Chain, a model of attack progression. Show where defenses worked or missed activity, and recommend prioritized controls that could interrupt attacks earlier.
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Convert a Notion specification into a linked implementation plan and manageable tasks. Extract requirements and acceptance criteria, record uncertainties, and keep task statuses, checklists, blockers, and milestone updates aligned as the work progresses.
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Continue an existing OpenSpec change by creating one next document. Check progress and dependencies, follow the workflow's template, and report what was completed and which documents are now available to create.
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Keep plans, research findings, and progress in Markdown files for multi-step work in Kiro. Read saved project records when resuming a task to recover goals, decisions, and recent actions.
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Organize complex work into phases and save plans, findings, and progress in project files. Keep separate task records and, on supported hosts, automatically bring the selected plan back into the agent’s working context.
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Use German-language guidance to organize multi-step agent work in Markdown files. Store plans, findings, and progress by task, then revisit those records to resume research, review decisions, and track unfinished phases.
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Keep plans, research findings, and progress in Markdown files for complex agent work. Separate task plans and automatic planning reminders help the agent recover saved context, track decisions, and identify the next action.
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Organize complex work into phases and save plans, findings, and progress in project files. Keep separate task records and, on supported hosts, automatically bring the selected plan back into the agent’s working context.
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Organize multi-step research and project work in Continue using Markdown files for plans, findings, and progress. When invoked, the skill reads saved planning context to support resuming work and reviewing earlier decisions.
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Organize multi-step research and project work with Markdown files for plans, findings, and progress. Gemini hooks, automatic actions at session events, surface planning context so the agent can resume from saved records.
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Organize multi-step agent tasks with persistent Markdown files for plans, findings, and progress. Records decisions, errors, and test results, then reloads the selected task's planning files to resume work after an interruption.
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