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Found 1,925 Skills
Debug Node.js/TypeScript/JavaScript applications using the agent-dbg CLI debugger. Use when: (1) investigating runtime bugs by stepping through code, (2) inspecting variable values at specific execution points, (3) setting breakpoints and conditional breakpoints, (4) evaluating expressions in a paused context, (5) hot-patching code without restarting, (6) debugging test failures by attaching to a running process, (7) any task where understanding runtime behavior requires a debugger. Triggers: "debug this", "set a breakpoint", "step through", "inspect variables", "why is this value wrong", "trace execution", "attach debugger", "runtime error".
Use when asked to compare multiple ML models, perform cross-validation, evaluate metrics, or select the best model for a classification/regression task.
Structured paragraph curation for C5: **select -> evaluate -> subset -> fuse**, so drafts converge instead of only expanding. **Trigger**: paragraph curator, curation, select evaluate fuse, paragraph selection, 选段, 评价, 融合, 收敛, 去冗余. **Use when**: you are in C5, `sections/*.md` exist, and the writing loop drifts toward 'longer by accumulation' (repetition, redundant paragraphs, weak synthesis). **Skip if**: evidence packs are thin / `evidence-selfloop` is BLOCKED; or you are pre-C2 (NO PROSE). **Network**: none. **Guardrail**: do not invent facts; do not add/remove citation keys; do not move citations across subsections; keep section-level claims consistent with `output/ARGUMENT_SKELETON.md# Consistency Contract`.
Create social media content assets with ready-to-use copy and visual direction. Use when user asks to create content, write captions, make posts, or generate social media assets. Triggers on - "buat konten", "content create", "buat caption", "/content-create" command, or requests to create specific social media posts with copy and visuals.
Architect and co-design futureproof persistence systems built on open data principles. Use when designing data layers, choosing storage formats, structuring knowledge bases, building file-system-as-database architectures, or evaluating existing systems for portability and longevity. Use when user says "design my data model", "how should I store this", "is my data portable", "audit my persistence layer", "plan a migration", or asks about file-based databases, Markdown schemas, or Obsidian-compatible data formats. Do NOT use for general coding tasks, database query optimization, or SQL schema design.
Use when "Dask", "parallel computing", "distributed computing", "larger than memory", or asking about "parallel pandas", "parallel numpy", "out-of-core", "multi-file processing", "cluster computing", "lazy evaluation dataframe"
Framework adoption decision matrix: custom vs large frameworks in the Claude Code era. Use when evaluating whether to adopt a large framework or build custom with AI.
Expert in designing, optimizing, and evaluating prompts for Large Language Models. Specializes in Chain-of-Thought, ReAct, few-shot learning, and production prompt management. Use when crafting prompts, optimizing LLM outputs, or building prompt systems. Triggers include "prompt engineering", "prompt optimization", "chain of thought", "few-shot", "prompt template", "LLM prompting".
Evaluate unit economics and capital efficiency for SaaS. Covers CAC, LTV, payback, margins, burn rate, Rule of 40, and magic number.
Generate, evaluate, and A/B test email subject lines for maximum open rates. Includes formulas for curiosity, urgency, personalization, and more. Trigger phrases: "email subject line", "subject line ideas", "email subject", "write subject lines", "A/B test subject lines", "improve open rates", "email open rate", "subject line formulas".
Deep web research with parallel investigators, multi-wave exploration, and structured synthesis. Spawns multiple web-researcher agents to explore different facets of a topic simultaneously, launches additional waves when gaps are identified, then synthesizes findings. Use when asked to research, investigate, compare options, find best practices, or gather comprehensive information from the web.\n\nThoroughness: quick for factual lookups | medium for focused topics | thorough for comparisons/evaluations (waves continue while critical gaps remain) | very-thorough for comprehensive research (waves continue until satisficed). Auto-selects if not specified.
Meta-cognitive decision support that analyzes current context and surfaces intelligent next-step options to the user. Use this skill when: (1) User explicitly invokes /checkpoint, (2) Significant work has been completed and a checkpoint is valuable, (3) Uncertainty or ambiguity exists about requirements or approach, (4) Task complexity has expanded beyond initial scope, (5) Before finalizing or committing to ensure nothing is missed. This skill pauses execution, assesses the situation holistically, and presents 2-5 contextually-appropriate options via AskUserQuestion, with a recommended option and rationale.