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Private, local Bale bot for agents: read, search and answer messages, ask and wait, files. Use when the user asks about Bale Bot (bale.ai) or wants to run their own Bale messenger bot in Iran.

Unofficial read-only Asal Banoo: search cosmetics and skin care, compare prices, sizes, deals. Use when the user asks about Asal Banoo (asalbanooshop.com) or wants cosmetics, skin and hair care or perfume in Iran.

Unofficial read-only 30book: search Iranian printed books, compare editions and prices. Use when the user asks about 30book (30book.com) or wants ebooks, audiobooks or printed books in Iran.

Direct and build professional motion design (promo and launch films, kinetic typography, animated explainers, social clips, title sequences) with correct Persian/Farsi and right-to-left typography, in Remotion or plain web code. Use this skill whenever the user wants a video, animation, motion graphics, teaser or animated text that contains Persian, Farsi, Arabic-script or RTL text, and whenever they say a motion piece looks "default", "like a slideshow", "AI-made" or "not pro", or that the Persian looks off, broken or disconnected, even if they never say "motion design". It brings the anti-slideshow method (one camera, objects that carry across scenes, music-first beat-locked edits), eight ready techniques with live sketches, HarfBuzz tooling for per-letter and per-dot Persian animation, kashida stretching, and a Persian correctness checklist and linter.

爆款拆解复刻：把抖音/TikTok 爆款带货视频（链接、转写或口述结构）拆成 8 维结构与 5-beat 节拍，再映射到你的商品，输出拆解表 + 3 个复刻角度 + 可渲染 storyboard.json。Use when the user says 爆款, 拆解, 复刻, 对标, 仿拍, viral remake, breakdown, swipe file, copy structure, 竞品视频, remake a TikTok/Douyin product video, or wants to replicate a viral ecommerce short's structure with their own product.

卖点分镜表：把商品卖点拆成 15–60 秒带货短视频的逐镜分镜表（时间码、画面、台词、字幕、花字、素材来源、运镜），并直接输出可渲染的 storyboard.json。Use when the user wants a storyboard, 分镜, 分镜脚本, shot list, 带货视频脚本, video script from selling points, or needs to plan a product video before generating or editing.

多模型镜头提示词适配：把一份分镜表改写成适合不同视频生成模型的提示词（中/英、首帧/首尾帧/纯文生视频、运镜词表、负面约束），模型中立、不编造价格或参数。Use when the user wants the same shot list adapted for Seedance, 可灵 Kling, Veo, Runway, Hailuo/海螺, Wan/通义万相, Sora, Pika or 'any video model', asks 怎么写视频提示词, camera movement terms, or a model returns deformed products.

3 秒钩子脚本：为电商短视频写前 3 秒开场（台词 + 画面 + 花字），按痛点/反差/结果先行/提问/数字/场景代入等钩子类型一次给出多版，并做合规自检。Use when the user asks for a hook, 开头, 黄金 3 秒, 前三秒, opening line, scroll-stopper, 完播率, or wants to rewrite a weak opening for 抖音 / TikTok Shop / 视频号 / Reels.

Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.

Cut AI tells from any writing. Must always apply.

TypeScript best practices. Use when reading or editing any .ts or .tsx file.

Layered technical-writing standard: Diátaxis structure, Google developer style sentences, STE instruction rules, Global English syntax. Use for /technical-writing or when writing or reviewing docs, RFCs, readmes, PR descriptions, or commit messages.

Explain a body of work plainly so a person actually understands it. Runs the `how` and `why` skills and weaves what they find into one clear explanation. Use for 'teach me this', 'help me really understand X', 'explain this change or subsystem to me'.

Use only when the user explicitly asks for TDD, a failing test, or a regression test, OR when the bug has an obvious cheap local test target. Skip when the test path is unclear, expensive, integration-heavy, or not requested.

Fan out N parallel workers, drain them, and return one report. Use for /swarm, 'swarm this', or parallel coverage, races, gauntlets, and exploration.

Configure which models p3-stack uses per role and at what reasoning budget. Detects your available models and writes p3-models.md, which overrides the skill defaults. Use for /setup-p3, "configure p3 models", "p3 budget", or changing p3-stack's model choices.

Reconstruct your recent working context from your own chat history, live state, and the shared record (user reports, prior fixes, incidents), then hand back a tight current-state brief. Use for 'recall my work on X', 'catch me up', 'what have I been working on', 'where did I leave off', before starting or resuming work.

Apply when designing types, reviewing a function signature, or writing code in any statically-typed language. Make illegal states unrepresentable, brand semantic primitives, parse external data at boundaries, refuse to lie to the compiler, exhaust variants, derive from authoritative schemas.

Apply when you write, change, or keep a test. Call the code the way its users do and assert the result they observe against a literal expected value. If the test would still pass when every imported function returns undefined, rewrite the assertion or delete the test.

Apply when sequencing an addition, refactor, or rewrite. Remove dead code, redundant validators, and stub references first, then build on the simpler base.

Apply to multi-step work (sweeps, migrations, runs of similar edits) and to how you stack commits and PRs. Break work into small units that each end in a verifiable state, check each before the next, and order delivery so the sequence proves itself to a reviewer.

Apply when concurrent actors might write to the same file, branch, key, or state object. Eliminate the sharing first; serialize structurally only when one shared writer is a real invariant.

Apply when integrating a new requirement into an existing design. Redesign as if the requirement had been a foundational assumption from day one, instead of bolting it on.

Apply after completing a task, before declaring done. Verify against the real artifact (run the feature, read the actual value, inspect the diff), not a proxy, self-report, or 'it compiles.'

Apply during planned rewrites and migrations with explicit phase boundaries. Converge on the target architecture; don't preserve smooth intermediate states with throwaway compatibility code.

Apply when tempted to ask 'should I do X?' on reversible work. Proceed, present the result, let the human course-correct after the fact; reserve confirmation for irreversible actions.

Apply when writing stateful logic, or when code branches a lot or repeats a shape assumption across files. Encode the domain in a structure instead of scattered conditionals.

Apply when reviewing or shaping code that's hard to trace. Count layers between question and answer, and hidden state in the reader's head; collapse one-caller wrappers and shrink mutable scope.

Apply when introducing a new internal API while old callers still exist. Migrate callers and delete the old API in the same wave instead of preserving compatibility layers.

Apply when designing commands, lifecycle steps, or processing loops that run amid crashes, restarts, and retries. Converge to the same end state regardless of partial prior runs.

Apply when refactoring, evaluating diff size, or tempted to add abstractions, layers, or signal threading. Bias toward deletion and the smallest change that solves the problem.

Apply when context is filling up: large outputs, long files, repeated reads, fan-out planning. Route bulk to delegated tasks; keep summaries in the main thread, not raw payloads.

Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.

Apply when debugging. Trace each symptom to its root cause and fix it there; reproduce first, ask why until you reach it, resist nil-check guards that silence crashes.

Apply before you trust, report, or act on a number you measured: a speedup, a regression, a throughput, a latency, or an eval result. Find what limits it, and rule out that it measured something other than the work you think.

Apply when product, UX, or feature-scope tradeoffs come up. Choose user delight over implementation convenience; ship fewer polished features over more rough ones.

Apply when facing a novel UI interaction or architectural decision with no precedent in the codebase. Build 2-3 competing prototypes and compare side by side before committing.

Apply when you catch yourself writing the same instruction a second time, or notice a recurring correction. Encode the rule as a lint, metadata flag, runtime check, or script instead of more text.

Apply to any non-trivial work, not just bulk work: edits, migrations, analyses, checks. Build the tool that does it or proves it (codemod, script, generator, or a skill your subagents follow) instead of working by hand. The tool is the artifact a reviewer can rerun.

Apply when wiring validation, error handling, or framework adapters. Concentrate guards at system boundaries (CLI, config, network, external APIs); trust internal types and keep business logic in pure functions.

Apply when two or more fixes that share one premise have failed the same gate. Take a census of which actors hold the imbalance before the next fix, then question the premise instead of writing another fix that assumes it.

p3 agent style for concise, detailed responses, deliberate delegation, unslopped prose, simple code, and verified work. Use for p3, /p3-mode, or requests to work in this style.

Guides users through p3-stack setup, /p3-mode, and picking the skill, playbook, or principle for a task. Use for /p3-help, or when the user asks how to install, set up, or use p3-stack, or which p3-stack skill fits. Not for requests to do work, even ones that name p3-stack.

Spawn Comment Sicko, fix accepted findings, and offer encodings for claimed constraints.

Use when building a custom UI (page, dashboard, buttons) that should wake the agent over a webhook, when the user must provide a webhook secret, or when exposing that UI on Tailscale.

Periodic pass that keeps a project's verification skill and feature map honest: parallel source readers per feature, one live session driving every feature, at most one PR of proven corrections. Use for /maintain-verification-skill or "audit the verify skill".

Use for "interrogate", "adversarial review", "multi-model review", "challenge this", "stress test this code", "find blind spots", or "tear this apart". Multiple LLM reviewers challenge changes from independent angles.

Use for "how does X work", code walkthroughs before changing something, and placement / ownership / layering questions ("where should this live", "which package owns this", "is this the right layer"). Explains subsystem architecture, runtime flow, onboarding mental models. Use why for motivation.

Design an auditable playbook when no narrower one fits: a large migration, an ambitious multi-part change, or work a human reviews after stepping away. Scales rigor to the task, runs a hypothesis loop, and logs decisions via show-me-your-work. Use for /figure-it-out, 'figure it out', a large migration, or when no narrower playbook applies.

Generate a project-local verification skill that drives your app the way a user does — any language, framework, or platform. Use for /create-verification-skill, "make a control skill for this repo", or when a project has no scripted way to prove UI/CLI/service behavior.

Find the mistakes agents keep repeating in this repo and make each one impossible. Try architecture first, then types, then a lint whose error names the fix, then a test, and write docs last. Prove each check fails on a real past mistake. Repeat this each time the operator corrects you. Use for /correct.

Restate the last message in plain human language, with no jargon.

Find what a change could break somewhere else before it ships, beyond the diff, and prove the one fact it's safe because of by running real code instead of writing it up. Use for 'blast radius of X', 'what could this break', or reviewing a small diff you don't trust.

Vet a perf measurement (limiter, tuning, limits, errors, repeatability, relevance, and whether the work happened) before you report or act on it. Use when you run a benchmark or report a speedup or regression you measured.

Use for "automate me", "create/update/refresh my -mode skill", "turn/capture my preferences or working style into a skill", or wanting agents to follow how the user works. Drafts or revises a personal -mode skill via the authoring-a-skill playbook + unslop, optionally pulling fresh evidence from recent threads.

Spawn N parallel candidates at the same task, pick a base, graft the strongest parts of the losers into it. Use for /arena, 'arena this', 'throw it in the arena', or when one attempt at a non-trivial artifact would lock in the wrong shape.

Sketch types, signatures, and module structure before code, then stay in the loop while implementation fills in. Use for /architect, 'architect this', 'design this', or non-trivial work where jumping to code would lock in the wrong shape.

Discover and compare Jev and TypeSafe SDKs, integrations, applications, and evaluations. Use when selecting public resources for a typed-decision workflow or checking what evidence exists for a Jev claim.

盒子原创行业研究 Skill 组合中的估值分析专项。选择适用的可比公司或交易、DCF/FCFF/FCFE、SOTP、资产、股利或里程碑情景方法，建立可复算的企业价值或股权价值区间、调整桥、敏感性和隐含预期。 用户直接要求“给上市或非上市企业估值”“为商业尽调、融资或并购测算价值”“判断交易对价、分部或早期项目估值”“做反向估值或估值合理性检查”等时独立启动；由 `hehe-industry-researcher` 派发任务卡时按组合模式执行。独立启动时自行确认范围、搜索并审核材料、分析和交付本专项结果。

盒子原创行业研究 Skill 组合中的趋势分析专项。判断行业、技术、需求或商业化变化所处阶段、驱动机制、核心变量、时间关系、经营后果与证伪条件。用于“分析行业趋势或未来走向”“判断技术扩散阶段”“研究供需、需求演变或景气变化”等问题。 由 `hehe-industry-researcher` 派发任务卡时按组合模式执行；用户直接提出上述趋势问题时独立启动，自行确认范围、搜索并审核材料、分析和交付本专项结果。