“defaults”的搜索结果

Your habits, imprinted on AI. Learns how you work from conversation, builds a portable profile, and applies judgment that adapts to you: when to act, when to check with you, when to follow the project's rules over your own defaults. Use this skill whenever the user starts a new session, opens a project, writes or reviews code, debugs, plans, or writes commits. If .dna.md does not exist yet, start the onboarding conversation before doing anything else. Active in almost every working session.

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Builds backend services and APIs with durable defaults. Use when implementing REST, GraphQL, tRPC, or gRPC services with auth, queues, data, or observability.

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Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.

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Gather phase context through adaptive questioning before planning. Use --all to skip area selection and discuss all gray areas interactively. Use --auto to skip interactive questions (Claude picks recommended defaults). Use --chain for interactive discuss followed by automatic plan+execute. Use --power for bulk question generation into a file-based UI (answer at your own pace).

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Govern mini-program release readiness and evidence across source branches, semantic versions, build artifacts, test flags, debug paths, sensitive data, permissions, privacy declarations, platform uploads, review submissions, staged versions, production releases, and rollback plans. Use when users ask for a release checklist, packaging, export, version bump, upload readiness, submission readiness, launch status, rollback preparation, or a precise judgment of what has and has not shipped. Defaults to read-only preflight, requires separate explicit authorization for every external state change, and never treats a Git push, successful build, platform upload, review submission, approval, or production publication as interchangeable.

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Systematic backlink building for indie founders. Covers 5 channel types ranked by GEO + SEO ROI: Wikipedia (entities), authoritative media (PR), industry reviews (G2/Capterra/Product Hunt), Reddit/Quora discussions, and HARO/Featured.com expert quotes. Designed for 0→1 sites where domain authority is the bottleneck. Aligns with 2026 Google/Bing GEO guidance: backlinks are the strongest brand-authority signal AI search engines use to decide citations. Defaults to dev/B2B link sources; for 2C products (education, consumer apps) authority links differ — see gingiris-seo-geo/references/2c-adaptation.md.

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Run the post-deploy send test that validates a freshly deployed or updated warp route end-to-end — real token transfers across the route's legs, delivery confirmation, and fee-accrual checks. Use when asked to send-test, round-trip, or validate transfers on a warp route. Defaults to a full collateral-mesh test for multi-collateral routes.

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Debug validator checkpoint inconsistencies where some validators are behind others. Use when alerts mention "checkpoint inconsistency", "validators behind", or "inconsistent latest checkpoints", or when asked to debug validator sets, investigate validator delays, or troubleshoot metadata fetch failures for a chain. Defaults to default_ism app context if not specified.

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Set up Prisma ORM in an application, connect its database, or troubleshoot the connection of an existing Prisma 6, 7, or 8 app. Defaults new applications to Prisma ORM 8 and loads the package-owned prisma-8 skill; keeps existing Prisma 6/7 apps on their version with provider references for PostgreSQL, MySQL, SQLite, SQL Server, CockroachDB, MongoDB, and Prisma Postgres.

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Use when parallel agents in a convoy or across git worktrees hit a write conflict on shared state — a git tree, a config, or a shared document — and you must decide whether the conflict is semantically real. Classifies each conflicting hunk as independent (keep both), redundant (pick one), or a genuine clash (escalate), instead of blind locks, abort-and-retry, or escalate-everything. Sits ABOVE refinery-merge and NEVER blind auto-merges: it wraps an LLM judgment, defaults to escalate on any uncertainty, and unconditionally escalates any hunk touching .planning/, config, credentials, or safety-critical paths. Backed by CoAgent (arxiv 2606.15376v1). Triggers on write conflicts between parallel agents on shared repo state.

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Reality tech (AR/VR/XR). Build and ship spatial experiences (WebXR/OpenXR/Unity/Unreal) with strong defaults for interaction, performance, comfort, privacy, and deployment.

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Shared Python 3.11+ development rules — type safety and the boundary policy for `Any` (ty, native generics, Protocol, TypeIs, Pydantic), layered architecture and SOLID, error handling, security, performance, identifier naming, PEP 723 script dependencies, Rich/Typer output, tooling defaults (uv, ruff, ty, hatchling, pytest), and testing requirements (behavioral coverage, TDD). Activates when any Python skill or agent needs the shared rules for implementation, code review, refactoring, or test authoring.

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Compose polished charts (timeseries, bar, line, area, pie, scatter, or anything else the data calls for) from tabular data using the chartkit primitives, producing PNG, SVG, or self-contained interactive HTML. Use when the user asks to chart, graph, plot, or visualize data and wants something better than raw matplotlib defaults.

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Analyze content performance patterns. Extract what works (hook types, formats, personas). Auto-update learned defaults so future content improves.

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Pythonic wrapper around RDKit with a simplified interface and sensible defaults. Preferred for standard drug discovery work — SMILES/SELFIES/InChI conversion, molecule standardization and sanitization, descriptors, ECFP and other fingerprints, Tanimoto distance matrices, Butina clustering and diverse subset picking, Bemis-Murcko scaffolds and scaffold splits, BRICS/RECAP fragmentation, 3D conformer generation, SDF/CSV/Excel and cloud I/O, and parallel processing via n_jobs. Returns native rdkit.Chem.Mol objects, so it composes with RDKit throughout. Also trigger on datamol, `import datamol as dm`, dm.to_mol, dm.standardize_mol, dm.cluster_mols, or dm.pick_diverse. For advanced control or custom parameters, use the rdkit skill directly.

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Gather and persist project design context such as audience, brand personality, UX goals, and implementation defaults for future better-web-ui work. Use when starting a project, defining UI direction, or establishing reusable design guidance before other better-web-ui skills.

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Extract reusable components, product patterns, and design tokens into a clearer design system with shared APIs, documented defaults, and better reuse. Use when the user wants to refactor repeated UI, consolidate buttons/cards/forms/sections, build a component library, or turn one-off values into reusable tokens.

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Detect hardcoded credentials, default passwords, fail-open configurations, insecure default settings, and other security misconfigurations that ship as default behavior in applications.

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Run an SDLC delegated workflow via Archon. Wraps the archon CLI with project-aware defaults.

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Scaffold a new Android app with SDLC and Play-safe defaults — Kotlin/Compose Gradle project with version catalog, convention plugins, module layout, a targetSdk that meets the Play mandate, R8 on release, and git-ignored signing so it passes the pre-flight checker from day one. Use when starting a new Android project.

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Scaffold a new iOS app with SDLC and submission-safe defaults — diffable project files, app + test targets, deployment-target policy, a git-stamped build number, and the Info.plist keys the pre-flight checker wants so the project passes TestFlight from day one. Use when starting a new iOS project.

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Audits and optimizes the five global Claude layers (User Preferences, Styles, Global Memory, Skills, MCP Connectors) using the Global Layer Scorecard (six dimensions, anchored 1-5 rubrics). Detects eight cross-layer failure modes and produces evolutionary recommendations (Promotion, Demotion, Codification, Skill Extraction). Use when user says "audit my global setup," "optimize my preferences," "review my Claude configuration," "check my cross-project setup," "are my preferences working," "clean up my global memory," or "what should be in my preferences vs my project." Also use when a user has 3+ Projects and wants to improve their shared foundation. Do NOT use for single-Project audits, Project Memory optimization, or full-stack audits (use rootnode-project-audit, rootnode-memory-optimization, or rootnode-full-stack-audit respectively, if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.

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Builds complete, optimized Claude prompts and Project scaffolds from task descriptions. Use when building, designing, creating, or structuring a Claude prompt or system prompt. Trigger on: "build me a prompt," "compile a prompt for," "create a system prompt," "write a Claude prompt," "design a prompt for," "help me write a prompt," "scaffold a Claude Project," "design a Project for." Uses a four-stage methodology (Parse, Select, Construct, Validate) and a tested 5-layer architecture (Identity, Objective, Context, Reasoning, Output + Quality Control). In Project Mode, the Compiler is global-layer-aware — checks User Preferences, installed Skills, and MCP Connectors to avoid redundancy and flag gaps. Do NOT use for auditing existing prompts (use rootnode-prompt-validation if available) or diagnosing existing Projects (use rootnode-project-audit if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.

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Audits and scores Claude Projects using a six-dimension Scorecard with anchored 1-5 rubrics and detects seven structural anti-patterns. When global layer info is provided, adds cross-layer alignment findings. Use when user says "audit my project," "review my custom instructions," "score my project," "evaluate my Claude project," "improve my system prompt," "what's wrong with my project," "why is my project underperforming." Also trigger on symptom-phrased: "my project doesn't work right," "Claude is inconsistent in my project," "my Project used to work and now doesn't." Also use when the user pastes Custom Instructions asking why output is poor or generic. Do NOT use when the user's primary request is a global-layer audit (use rootnode-global-audit if available), single-prompt evaluation (use rootnode-prompt-validation if available), or Memory-only optimization (use rootnode-memory-optimization if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.

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