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Suede Slop Stop: Suede Labs context-aware anti-slop pass for finished prose. Find or remove generic filler, manufactured emphasis, false agency, formulaic structure, chat and draft residue, and formatting applied by rule, without flattening the author's voice. Use before copy, a README, an email, a social post, or a doc ships; after a long assisted-writing session; or for a findings-only slop audit. NOT FOR: writing new copy (use suede-copy); deciding whether a person or model wrote text; changing or certifying facts, which require primary evidence.

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Suede Labs agent-team orchestrator: split complex work into coordinated lanes with explicit file ownership, WIP collision detection, quality gates, escalation thresholds, rollback plans, and handoffs that prove what shipped. Use when one shared change needs safe parallel ownership across builders and reviewers, when a lane map must be resolved before anyone opens a file, or when running a repeatable public-repository contribution program with issue scoring, atomic task leases, isolated worktrees, and explicit publication authority. NOT FOR: one repo change a bundled DAG can run end to end (use suede-graph-flo-xr); findings-only review of a diff (use suede-code-review) or an A-F ship grade (use suede-code-grader); CI, branch protection, or merge-gate wiring (use suede-ci-gate); branch and worktree setup on a stale mirror (a private Suede Labs companion, not in this pack).

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Suede-affiliated Amazon money-recovery audit for restocking fees, short or denied refunds, and Amazon-billed subscriptions. Use when the user mentions a restocking fee, a short or denied Amazon refund, or a forgotten Prime Video Channel, Audible, Kindle Unlimited, or Prime charge, or asks whether Amazon still owes or bills them. Read-only discovery; no chat, cancellation, or dispute without the account owner's per-item confirmation, and never a promise of recovery. Requires an authenticated Claude in Chrome session. NOT FOR: bank chargebacks, marketplace A-to-z seller claims, price-protection claims, or subscriptions billed outside Amazon (use subscription-recovery).

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Suede AI findings-only code review with full context: changed files, callers, contracts, and deploy surface. Covers TypeScript, React, Next.js, database, Swift/iOS, OWASP, accessibility, SEO, observability, commit hygiene, and deploy risk, ranked P0-P3 with file:line evidence and a fix path. Use when asked to review a diff, PR, branch, or commit range, find the bugs before merge, check a change for security or accessibility problems, or judge whether a change is safe to deploy. Emits findings and a ship gate, not a grade. NOT FOR: the A-F letter grade alone (use suede-code-grader); findings plus grade in one pass (use suede-code); making CI enforce the result on every merge (use suede-ci-gate); root-causing a live bug or failing test (a private Suede Labs companion, not in this pack).

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Full health check of all your skills in one report. Use when the user wants to check for errors, find duplicates, detect broken skills, or get a complete overview of skill health. Pass --brief for inventory only. Trigger with '/janitor-report'.

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Use this skill to create fillable Word forms (.docx) with real Content Controls (SDT) + legacy FormField checkboxes + MERGEFIELD mail-merge placeholders + document protection. Trigger on: 'fillable form', 'form fields', 'content controls', 'SDT', 'word form', 'fill in', 'only editable fields', 'protect document', 'onboarding form', 'HR intake', 'survey template', 'contract / SOW template', 'mail-merge template', 'compliance checklist', 'medical intake questionnaire'. Output is a single .docx where specific fields are editable and the rest is locked. This skill is INDEPENDENT, not a scene layer on docx — payload is `<w:sdt>` + `<w:ffData>` + `<w:fldChar>` + `documentProtection`, none of which docx base skill covers. Do NOT trigger for regular reports, letters, memos, academic papers, pitch decks, or any document with no user-fillable fields — route those to officecli-docx or its scene layers.

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Skill Base server deployment guide. Covers starting the Skill Base server (npx skill-base), Docker configuration, port mapping, SQLite database backup, and platform capabilities (collections, tags, GitHub import). For deploying and operating the Skill Base platform itself only.

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Show or change the Cassette editing model and thinking level for the current media session. Invoke only when the user explicitly asks for the model picker, wants to inspect the current Cassette model, or requests a model/thinking change.

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Edit, trim, cut, caption, subtitle, reframe, combine, add background music to, or export video, audio, and image files through Cassette. Use this skill whenever the user asks to change, preview, or render a media file in the project — even if they never say "Cassette" or name a tool — for example "trim the intro off demo.mp4", "add subtitles to this clip", "make me a 30-second cut with music", "why is there dead air at the start". Drives the local Oh My Cassette stdio MCP tools in Codex or Claude as one multi-turn conversation with the Cassette agent, with per-turn timeline previews, guided questions, and rendering only on explicit export.

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Implement, build, create, or add any feature, endpoint, page, component, or functionality. Use this skill whenever the user asks you to write new code or make code changes — whether it's adding an API endpoint, building a UI page, creating an export feature, wiring up a webhook, implementing a search/filter, or any other hands-on coding task. This is the default skill for all 'build this', 'add this', 'create this', 'wire up', 'implement' requests. Covers the full cycle: clarify requirements, plan if needed, write code, verify, and review. Do NOT use for pure research, debugging, documentation, or explanation — only when the user wants working code delivered.

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Use this skill for any Python backend work in this project: building FastAPI endpoints, writing service functions, defining Pydantic/SQLModel schemas, running Alembic migrations, or debugging 422 errors. Essential for authentication and authorization patterns — setting up get_current_user, is_superuser checks, admin-only guards, role-based access, and dependency injection chains like Depends(). Also covers middleware, background tasks, async SQLAlchemy sessions, ORM relationship loading, and request/response design. Activate whenever the question involves Python API code, FastAPI patterns, or backend architecture in this codebase. Not for frontend, Docker, CI/CD, or infrastructure.

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Use when the diff changes a GitHub Actions workflow, a reusable action, a CI cache or artifact handoff, a Dockerfile or compose file, Terraform/HCL, Kubernetes manifests or Helm values, an environment overlay, a workload identity binding or a cloud OIDC trust policy - judged only where concretely exploitable

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Use when a game task could run on more than one engine or the repository has no engine yet - read the repo's engine and pinned version, and only for a brand-new game pick one from platforms, 2D/3D, team language, scale and licensing.

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Use when writing Godot 4 GDScript - static typing everywhere, scene composition with component nodes, call down/signal up, @onready caching, Resources as data duplicated per instance, autoloads only for services, state machines, pooling, physics in _physics_process, and threaded loading.

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Use when building or changing features, preprocessing, encoders, resampling or train/validation/test splits — keep every fitted transform inside a Pipeline fitted on training folds only, and build time and group features without seeing the future or the same entity twice

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Use when planning a delivery request as the only orchestration agent - one board-writing subtask, backlog first, one approval question, then move approved tasks to todo

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Use when a batch (desktop or mobile) release reaches awaiting_verdict or was rolled back - read-only checks that the published artifact really exists and is served, and the exact yank step for a bad tag

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Use when ordering board tasks - set priority/blocked_by/deploy_depends_on by severity and dependency, split MoSCoW within a feature, and use RICE/ICE only for a genuine "what next" call across several features

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Use when a stakeholder sends a request - route it to backlog tasks, an analiz task, or a focused question, decide ask-vs-assume with a Definition of Ready, and ask only what a wrong guess would actually cost

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Use when Java is chosen but Quarkus does not fit - build the service with Spring Boot using the same clean layering, only when a required library lacks a Quarkus extension or the repo already standardizes on Spring

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Use on every UI change - semantic HTML, labels for controls, keyboard-navigable dialogs/menus, visible focus, and never color as the only signal

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Subscribe to live Hyperliquid data over WebSocket from the desk computer - mids, order book, trades, candles, best bid/offer, and per-account fills, order updates and events - with raw JSON, Python SDK and TypeScript examples, plus how to run a supervised watch that logs to a file and alerts. Read-only. Use for monitoring, fill notifications and any watch that polling would make expensive.

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Read live Hyperliquid market data from the desk computer with curl or the Python SDK - mid, mark and oracle prices, order book depth, funding (current, predicted, historical), open interest, volume, candles, perp and spot metadata, margin tiers, and how to save datasets for the strategy lab. Read-only, no key. Use for any market brief, depth read, funding question or data pull.

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What the desk does when something goes wrong on Hyperliquid - unknown send results, unexpected fills or positions, unprotected positions, stuck or orphaned orders, API outages, rate limiting, and suspected API wallet compromise. Contain first, reconcile from the exchange record, act only through approved tickets, then review. Use the moment anything does not match the ticket.

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。