8,322 件 ・ 関連度順
概要と使いどころ
Start a new Flywheel planning round. Produce initial markdown plan, route to competing frontier models, synthesize hybrid, refine 4–5×. Use before any coding begins on a new feature.
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 Forge's canonical verification chain (format:check + lint + typecheck + build + test). Use before claiming any task complete or opening a PR.
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 Forge's canonical verification chain (format:check + lint + typecheck + build + test). Use before claiming any task done or opening a PR.
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 the full Forge verification suite (format:check + lint + typecheck + build + test). Use this before claiming any task complete or before opening a PR.
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。
Scaffold a new Forge tool — implementation, registration, permission/risk metadata, sandbox routing, and a unit test. Use when adding anything to src/tools/.
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。
Merge duplicate or excessively overlapping beads in .beads/beads.jsonl into canonical ones. Run after any batch where 20+ new beads were created.
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。
Scaffold a new Forge tool end-to-end — type, implementation, registration, permission/risk classification, and unit test. Use when adding anything to src/tools/.
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。
Deep code review after beads have landed — random exploration + cross-agent review, alternating. Use every 30–60 min during active implementation, or after any epic lands.
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。
Scaffold a new Forge subagent (planner/architect/executor/reviewer/debugger/memory-style). Use when adding anything to src/agents/.
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。
Scaffold a new model provider for Forge — class implementation, registry wiring, providerEnum entry, local-catalog classification, and unit test with mocked transport. Use for anything under src/models/.
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。
Remove telltale AI-writing patterns from README, docs, and user-facing text. Must be done line-by-line, manually. No regex. Use after agents write any user-visible prose.
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。
Use when a task spans multiple steps, files, or unknowns — before planning the order of work, whenever about to report completion or success in any wording, and when picking the next action after a result, failure, or surprise. Also under deadline pressure, or when resuming work built on questionable foundations.
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 a reusable opportunity-to-artifact workflow: discover unmet needs, set up workspace factories, schedule recurring commander/worker/reporter prompts, batch-refine many items, optionally use SQLite state, build small artifacts, review quality, and track outcomes. Use when the user wants to repeatedly create apps, games, products, content, or experiments from market/user needs.
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。
Takes a proofread or apsa-style report file (or any markdown file using **Original:** / **Recommended:** syntax) and rewrites the original source file with git merge conflict markers so the user can accept or reject each suggested edit using VS Code or Positron's built-in merge conflict UI. Branch names are "original" and "claude-edits". Use when asked to apply edits, insert conflict markers, or set up merge resolution for a copy-edit report. Supports an optional @sec-label argument to restrict markers to one section.
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。
Redistricting analysis in R using the redistverse ecosystem. Use whenever the user is working with redist, redistmetrics, ggredist, geomander, adj, alarmdata, PL94171, censable, easycensus, tinytiger, baf, rict, or redistio. Covers the complete pipeline: Census and spatial data loading, adjacency graph construction, SMC/MCMC simulation, constraints (population balance, county splits, VRA compliance), convergence diagnostics, plan metrics (compactness, partisan fairness, splits), visualization, summary tables, and interactive plan drawing. Invoke whenever the user mentions redistricting, gerrymandering, district plans, simulation ensembles, or any redistverse package 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。
Apply the Acme house style to any prose - short sentences, no hype, lead with the answer. Shared across agents.
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。
Super Base Context — project doc loader & synchronizer. Triggers even without explicit "load docs"/"sync docs." READ MODE — load architecture/modules/coding/decision docs when work references project state: code work (write/modify/remove); design (features/APIs/schemas/architecture); review (modules, past solutions); tech selection; ADR research; migration/refactor planning; performance/security analysis; tests; code reviews; any spec/plan/design/ADR referencing project. WRITE MODE — NET DELTA vs. last doc sync: additions/modifications/REMOVALS/deprecations of previously-synced code or decisions (docs revert: delete BCU file/ADR), AND rollbacks. User signals: sync docs/done/ready to commit/pre-commit/record decision. Auto-fires before final task-completion reply. WRITE MODE does NOT fire on: brainstorming, generic/read-only Q&A, in-session try-and-undo with no net change, already-synced.
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。
Use when asked to brainstorm, evaluate whether an idea is worth building, run office hours, or think through a new product idea or design direction before any code is written.
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。
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output. Use when a task requires complete code or exhaustive unabridged output without placeholders.
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。
Draft blog posts, social media, email newsletters, landing pages, press releases, and case studies with channel-specific formatting and SEO recommendations. Use when writing any marketing content, when you need headline or subject line options, or when adapting a message for a specific platform, audience, and brand voice.
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。
"Calculate and analyze promotional ROI including incremental sales lift, margin impact, and promo type comparison. Use this skill when the user needs to evaluate whether a promotion was profitable, compare promotion types, simulate promo scenarios, or optimize promotional spending — even if they say 'was this sale worth it', 'which promo type works best', 'are we giving away too many discounts', or 'plan our next promotion'.".
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。
Research a prospect then draft personalized outreach. Uses web research by default, supercharged with enrichment and CRM. Trigger with "draft outreach to [person/company]", "write cold email to [prospect]", "reach out to [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。
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.
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。
"Measure and optimize customer service performance using CSAT, NPS, CES, First Contact Resolution, and text mining on support tickets. Use this skill when the user needs to evaluate CS team performance, identify top complaint drivers, optimize staffing, or build CS dashboards — even if they say 'is our CS team doing well', 'what are customers complaining about', 'how many agents do we need', or 'build a CS dashboard'.".
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。