2,059 件 ・ 関連度順
概要と使いどころ
When the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy. Also use when the user mentions 'referral,' 'affiliate,' 'ambassador,' 'word of mouth,' 'viral loop,' 'refer a friend,' or 'partner program.' This skill covers program design, incentive structure, and growth optimization.
日本語の概要は準備中です。原文の説明を表示しています。
AI knowledge engine - a memory system in 6 lines of code. remember/recall/forget/improve loop, vector + graph search, OpenClaw plugin supported.
日本語の概要は準備中です。原文の説明を表示しています。
Generate clean, playful low-density isometric voxel icon illustrations and explicitly requested four-frame physically credible loops built from large opaque face-lit acrylic blocks on an exact
日本語の概要は準備中です。原文の説明を表示しています。
Animate objects, cameras, lights, and properties in Blender — keyframes, F-curves, easing (Bezier, Linear, Sine, Bounce, Elastic), shape keys (morph targets / blendshapes / visemes), drivers (Python expressions on properties), NLA actions for reuse and layering. Use whenever the user asks to "animate this", "make it move / rotate / scale over time", "add keyframes", "loop / oscillate", "shape key / morph / blendshape", "visemes for lip sync", or any time-based property change. Make sure to use this skill even if the user does not say "animate" — also covers "spin it slowly", "make it wave", "fade in / out", "pulse", "facial expression".
日本語の概要は準備中です。原文の説明を表示しています。
Launches a saved multi-agent workflow by id on Claude Code or Codex. Use when the user asks to run a saved workflow or review loop.
日本語の概要は準備中です。原文の説明を表示しています。
PID/MPC/Kalman/anti-windup control primitives for feedback loops. Use when an autoscaler flaps, a controller overshoots after saturation, or budget pacing overspends at peak.
日本語の概要は準備中です。原文の説明を表示しています。
Builds a GPT and BPE tokenizer from scratch. Use when implementing autograd, attention, a nanoGPT loop, muP hyperparameter transfer, WSD annealing, loss spikes, or mid-training.
日本語の概要は準備中です。原文の説明を表示しています。
AI agent architecture, graph and loop composition, protocol choice, evaluation, and observability. Use when scoping or reviewing systems before implementation.
日本語の概要は準備中です。原文の説明を表示しています。
Designs and runs agent hives and multi-agent waves. Use when setting hive roles, code gates, dependency-graph fan-out, or verifier, vote and loop-until-dry passes.
日本語の概要は準備中です。原文の説明を表示しています。
Implements behavior changes with a test-first red-green-refactor loop: write one meaningful failing test, watch it fail for the intended reason, make the smallest change, then refactor while green. Use for new behavior, bug fixes, refactors with preserved contracts, and regression tests. Not required for disposable prototypes, generated files, or documentation-only edits.
日本語の概要は準備中です。原文の説明を表示しています。
Improve a skill using a test-fix-retest loop. Runs static checks, proposes targeted fixes, rewrites the skill, re-tests, and keeps or reverts based on score change.
日本語の概要は準備中です。原文の説明を表示しています。
Close the learning loop — record reward signal for an action AgentDB suggested. Use after using anything from agentdb_pattern_search / reflexion_recall / skill_search / learning_route. The bandit needs the signal to improve.
日本語の概要は準備中です。原文の説明を表示しています。
Collecting user feedback via NPS surveys, review analysis, sentiment analysis, feedback classification, and insight extraction reports. Use when establishing feedback loops.
日本語の概要は準備中です。原文の説明を表示しています。
Orchestrating design-to-implementation pipelines (code to visual to code closed loop), persisting a project design system across agents. Not for a single prototype (Forge) or direction only (Vision).
日本語の概要は準備中です。原文の説明を表示しています。
Optimizing frontend (re-render, memoization, lazy loading) and backend (N+1, indexing, caching, async) performance, plus continuous auto-tuning loops for GC/threadpool/cache/worker settings.
日本語の概要は準備中です。原文の説明を表示しています。
Create detailed phase plan (PLAN.md) with verification loop
日本語の概要は準備中です。原文の説明を表示しています。
Design a wise systems intervention from an existing analysis. Maps proposed actions against Meadows' leverage points, checks for unintended consequences, and generates alternatives.
日本語の概要は準備中です。原文の説明を表示しています。
Diagnosis loop for bugs and failing behavior. Use for errors, stack traces, regressions, failed tests, issue-tracker bugs, stuck investigations after failed fixes, or asks to debug/fix a bug.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy. Also use when the user mentions 'referral,' 'affiliate,' 'ambassador,' 'word of mouth,' 'viral loop,' 'refer a friend,' 'partner program,' 'referral incentive,' 'how to get referrals,' 'customers referring customers,' or 'affiliate payout.' Use this whenever someone wants existing users or partners to bring in new customers. For launch-specific virality, see launch.
日本語の概要は準備中です。原文の説明を表示しています。
Run metric-driven optimization loops. Use when improving measurable outcomes such as search relevance, clustering quality, build performance, prompt quality, or scored behavior through experiments.
日本語の概要は準備中です。原文の説明を表示しています。
Drives development with tests using the red-green-refactor loop. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality.
日本語の概要は準備中です。原文の説明を表示しています。
Runs the evals of a BMad skill through the agent harness the user works in and reports what they show: baseline against the bare model, variant against a stripped or prior version, quality against a rubric, and trigger accuracy of the description with an optional optimization loop. Use when the user asks to evaluate, benchmark, test the triggers of, grade, or compare versions of a skill, or when the bmad-toolsmith skill asks for an eval of a skill it built.
日本語の概要は準備中です。原文の説明を表示しています。
One iteration of an unattended development loop. Use when invoked by name
日本語の概要は準備中です。原文の説明を表示しています。
Multi-source research with citations using You.com. Use for questions that need several sources compared and synthesized, such as library or framework comparisons, tool and vendor evaluations, market research, or deep-dive reports. Routes between a cost-conscious agentic search loop and the one-shot `you-research` MCP tool.
日本語の概要は準備中です。原文の説明を表示しています。