Product & Planning

jasonxzwen Skill

Load when a task needs explicit OpenSpec exploration, discovery, or requirement clarification; use the repository's normal development contract for default change alignment.

jperrello Bundle

Per-clip upload-readiness grade (0-99) read off a FINISHED .mp4 plus its persisted sidecar plans — the first skill that inspects a delivered pixel-level artifact, the on-disk proxy for YouTube's VVSA swipe gate. Deterministic retention-proxy floor (frame1_is_face, letterbox_bars, credit_lit_at_open, first_visual_change, first_payoff_offset, longest_static_gap, opening_caption_words, max_residual_silence, terminal_loop_score) with hard caps (letterbox / face_withheld / credit_at_open / blocking_card / dead_tail) that cap grade≤40, plus ONE batched Claude rubric call (hook↔payoff / open-loop / cold-context) skipped when GRADE_SKIP_CLAUDE=1. Runs at the END of the per-span chain (after save-local) AND standalone over the whole output/ backlog (--backlog → output/_triage.json). Emits clip_NN.grade.json per the locked SELECTION-SUITE-CONTRACT schema. Idempotent (.gcmeta), non-fatal (any error → DROSS/empty, exit 0).

jperrello Bundle

An agentic, vision-driven final QA/repair pass — a Claude "director" WATCHES the finished short (a contact sheet of frames sampled across the whole clip + the transcript + the sidecar plans) and decides, in natural language, what is broken ANYWHERE (cold open, dead/rambling tail, a tonally-wrong b-roll match, a wrong-person punch-in, mistimed captions, a too-hot music bed, a flat hook) — not just the cold open, not just a fixed route vocabulary. It then APPLIES the fixes it can from a bounded, pixel-safe set (tail_trim via cut-clip; music_down via a bg-music re-mix) and SURFACES everything else as an honest edit list, re-reviewing up to DIRECTOR_MAX_ITERS times. Layered ON TOP of grade-clip (the cheap proxy floor) + fix-cold-open (the closed-vocab cold-open repair). NON-FATAL, idempotent (.dpmeta). Two modes — preventive in-chain (the pre-mix .ctaed.mp4 + clip_NN.* sidecars are co-located, so music_down can re-mix) and curative standalone/backlog (a finished output clip → tail_trim only, everything else surfa

jperrello Bundle

Deterministic source-video discovery — the clip-channel "outlier" method, keyless. Searches seed niche queries via yt-dlp ytsearch, prefilters to long-form candidates, fetches full metadata, and ranks by outlier score (views/day velocity, views-per-subscriber ratio, comment engagement, replay-heatmap peakiness). Emits a ranked candidates.json to pick the next pipeline source from. No Claude call, no API key.

ralvarezdev Skill

Upstream feature planning — requirement clarification, constraint discovery, design outline, vertical-slice task breakdown ordered by risk. Hands off to grill-with-docs and tdd. Use when starting new feature work from a vague request and no plan exists yet; if a plan or design already exists, use grill-with-docs to stress-test it instead.

risadams Bundle

End-of-sprint stakeholder report comparing the start.canvas (planning) to end.canvas (sprint close). Produces a markdown report fitting the standard SM template (Scrum Master, Sprint Accomplishments, Feature Demos, Customer Meetings, Status, Sprint Commitment, PI Confidence, Impediments). Applies team-specific overhead, wedge-balancing, and in-review overhead rules. Auto-runs a clarity-council session (statistics-expert + scrum-master + product-owner) for accomplishments/status/impediments synthesis. Use when user says "sprint review", "end of sprint report", "sprint stakeholder report", "sprint close report", or invokes /sprint-review.

santoshkanthety Skill

Interactive BPA rule generation for Power BI semantic models; guided discovery, model investigation, and expert rule authoring. Automatically invoke when the user mentions "BPA rule", "Best Practice Analyzer", or asks to "create a BPA rule", "audit BPA rules", "recommend BPA rules", "set up BPA for my team", "check model for best practices", "validate BPA rules", "improve a BPA expression".

santoshkanthety Skill

Step-by-step workflow for creating complete Power BI reports from scratch using pbir CLI. Covers model discovery, report creation, page layout, theme setup, visual placement, field binding, filtering, formatting, validation, and publishing. Automatically invoke when the user asks to "create a new report", "build a report from scratch", "make a dashboard", "set up a report with KPIs", "create an executive dashboard", "add pages and visuals to a new report".

mvschwarz Skill

Quickly capture product ideas, feature requests, or insights from meetings and conversations. Rapid documentation with smart categorization and deduplication.

mvschwarz Skill

Use when a specific `rig` command, subcommand, or flag is already known and you need its exact syntax, JSON shape, defaults, or error meaning. NOT for natural capability discovery, open-ended how-do-I questions, or choosing which OpenRig move applies.

yangwhale Bundle

Generate a comprehensive multimodal HTML explainer document with embedded Gemini TTS voice narration segments, structured sections, callouts, diagrams, and tables. Optimized for explaining complex technical topics (PoC briefs, new domain concepts, architecture deep-dives) to first-time learners who need both written reference AND spoken walkthrough. Use when the user says "做个讲解文档"、"多模态讲解"、"配语音讲解的文档"、"科普文档加语音"、"explain this with voice"、"technical walkthrough"、"语音讲解 HTML"、"多模态科普", OR when a topic is complex enough that an audio walkthrough materially helps comprehension (50+ concepts, multi-stakeholder, first-time exposure).

rohitg00 Skill

Workflow 1 adaptation for robotics and embodied AI. Orchestrates robotics-aware literature survey, idea generation, novelty check, and critical review to go from a broad robotics direction to benchmark-grounded, simulation-first ideas. Use when user says \"robotics idea discovery\", \"机器人找idea\", \"embodied AI idea\", \"机器人方向探索\", \"sim2real 选题\", or wants ideas for manipulation, locomotion, navigation, drones, humanoids, or general robot learning.

onedro1d Bundle

Interactive requirements gathering that produces machine-executable specs for microservices. Guides conversation through structured rounds to produce a complete requirements doc where every section maps to a code artifact (SQL, Zod schemas, handlers, tests). Triggers on "new feature", "new service", "requirements", "I want to build", "let's spec out", "define requirements".

lionkiii Bundle

Strategic SEO planning for new or existing websites. Industry-specific templates, competitive analysis, content strategy, and implementation roadmap. Use when user says "SEO plan", "SEO strategy", "content strategy", "site architecture", "SEO roadmap", "keyword strategy", "content calendar", "site architecture plan", "SEO budget", or "SEO timeline".

jperrello Bundle

Write output/<slug>/_selection.json for a source — the shipped shorts (scores + rationale from segments.raw.json, linked to their delivered filename) ALONGSIDE the considered-not-shipped RLM candidate menu (candidates.hint.json, each marked picked/unused) and the topic list (topics.json). Deterministic, no Claude, idempotent, non-fatal. Runs once at end of run AND standalone over the whole output/ backlog. Answers "show me the other arguments alongside the shorts".

lazygophers Bundle

对抗式审查 (红队, 非审批)。planning 产物 (prd 主入口/design 详细设计/findings 调研 + task.json 子任务) confirm 前硬门、或用户显式 "grill/盘方案/审设计/红队" 时使用 — 多轴逼问挖漏洞/隐藏假设/未定边界, 逐问给推荐答案+codebase 先查, 弱点表交用户裁才放行。main 亲做 (交互式)。

lazygophers Skill

➕ 规划级入口 (只规划不执行): 把指定请求纳入 trellis task 的 planning 阶段 —— 判新旧 + task.py create 登记 + 交互式 planning (brainstorm 主导 + grill 硬门1 边问边写), 产出 prd/design/implement 后停在 task.py start 之前, task 留 planning 态, 禁 exec/check/finish。用户想"先看规划再决定执行 / 添加分析规划任务 / 只规划不动手"时用。仅显式调用 (/trellisx-add), 禁 model 自动触发。与 trellisx-flow 边界: flow=强制全闭环 (plan→exec→check→finish), add=只到 planning 停; 执行 pending 规划态 task 走 /go

lazygophers Bundle

🔥 对抗式审查 trellis 任务工件 (prd / design / implement / spec / subtask 文件), 贯穿 plan 前/中/后全程逐分支 stress-test 设计树, 帮用户确认/审查/拆解需求。逐问审 (可一次多问批量确认提效 + 推荐答案 + codebase 能答先查), 产物 = 工件内联批注 + 弱点表 (不改写工件, 由 orchestrate/spec 决定怎么改)。独立全周期可调, plan 前 / planning 中 / start 前 / spec 重构前 / 任意决策点都能用。源于 grill-me (relentless interview) + 项目盲点实证

lazygophers Bundle

🎯 在 Trellis 项目 planning 阶段, 指导编写 task 文件夹内的 prd.md / design.md / implement.md, 把任务编排理念 (五要素拆分、执行层选择、资源互斥、失败回退) 内嵌到文档中。让后续 dispatch 与执行有据可依, 而不是写完 PRD 才临时想怎么拆

mannnrachman Bundle

Create, update, or validate a PRD. Use when the user wants help producing, editing, or validating a PRD

mannnrachman Bundle

Condense any input — an idea, brief, PRD, transcript, or mixed notes — into a short spec: SPEC.md plus supporting files that downstream skills build from. Also updates and validates existing specs, and can break a spec into stories. Use when the user says "create a spec", "distill this into a spec", "validate this spec", "update the spec", or "break this into stories"

mannnrachman Bundle

Test a product concept with Amazon's Working Backwards method: write the press release for the finished product first, then answer hard customer and stakeholder questions, ending in a complete PRFAQ document. Use when the user requests to 'create a PRFAQ', 'work backwards', or 'run the PRFAQ challenge'

mannnrachman Bundle

Product manager for PRD creation and requirements discovery. Use when the user asks to talk to John or requests the product manager

mannnrachman Bundle

Deprecated — forwards to bmad-prd (update intent)

mannnrachman Bundle

Deprecated — forwards to bmad-prd (create intent)

mannnrachman Bundle

Deprecated — forwards to bmad-prd (validate intent)

mannnrachman Bundle

Assess the impact of a significant change during sprint execution across the PRD, epics, architecture, and UX documents, and produce a sprint change proposal. Use when the user says "correct course" or "propose sprint change"

openshift Bundle

Use when the user asks to mine the disposition ledger for confirmed true positives, build or refresh the rule-calibration corpus, find rule-pack coverage gaps, check per-rule precision, or produce the opengrep rule-authoring backlog — e.g. "mine the ledger", "what TP clusters have no rule", "how precise are the traust rules", "refresh the rule-mining report". Runs out-of-band from audits; audits themselves feed it via structured scanner_correlation entries.

openshift Bundle

Triage a batch of raw security findings. Verify each is real, collapse duplicates, re-rank by derived exploitability, and tag with an owner. Takes a directory or file of scanner output and writes <repo>-triage.json + <repo>-triage.md sorted by what actually needs engineering attention. Use when asked to "triage findings", "validate scanner output", "prioritize vulns", or "review the backlog". Runs interactively by default; pass --auto to skip the interview.

openshift Skill

Use before committing any new or edited skill to the traust repo, or when asked "are the skills aligned", "did my skill drift from the conventions", "run the alignment check" — runs python3 -m traust.cli check skill-alignment, the cross-skill contract guard the pre-commit hook enforces. Verifies referenced scripts exist, deterministic pre-scan recording conventions (deterministic_steps, judge protocol) travel with the tools that require them, audit-profile skills link the shared report structure instead of restating it, liveness consumers name the census artifact, skill frontmatter matches its directory, and discovery wiring (.claude/.crush symlinks + command wrapper) is complete.

jonathan-vella Bundle

**ANALYSIS SKILL** — Azure Policy discovery: effective assignments (incl. MG-inherited), definitions/exemptions, effect classification, emits governance-constraints JSON. WHEN: 'Azure policy discovery', 'effective policy assignments', 'governance constraints', '04g-Governance Phase 1', 'refresh governance JSON'. DO NOT USE FOR: artifact writing, architecture mapping.

jonathan-vella Bundle

Look up Microsoft API references, find working code samples, and verify SDK code is correct. USE FOR: Azure SDK method verification, .NET/Python package lookups, code sample discovery, error troubleshooting, catching hallucinated methods and deprecated patterns. DO NOT USE FOR: conceptual documentation (use microsoft-docs), skill creation (use microsoft-skill-creator), Bicep/Terraform module lookups (use azure-bicep-patterns or terraform-patterns).

jonathan-vella Bundle

Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).

jonathan-vella Bundle

Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.

jonmumm Bundle

A multi-agent AI development workflow. Front-loads planning questions (grill-me), then launches parallel agents in Git worktrees: a Feature agent builds from a backlog via TDD, while CRAP, Mutation, and Acceptance agents continuously harden the codebase using deterministic metrics. Use when the user says "swarm", "run the swarm", "kick off a swarm", or wants to plan and then execute a long-running multi-agent run.

jonmumm Skill

Invoke this skill anytime you are creating a plan—such as crafting an RFC, writing a PRD, starting a new app, or proposing an architecture change. It will relentlessly interview the user to resolve all dependencies and edge cases.