Other skills

Transform vague product ideas into evidence-anchored problem statements for PRD v0.1 Spark. Triggers on starting new products/features, validating market opportunities, drafting PRD Why sections, or requests like "frame the problem", "define pain points", "write problem statement", "start v0.1", "what problem are we solving". Outputs structured problem tables with CFD evidence IDs.

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Detect template version drift and guide migration to the latest template version. Compares current repo against the template, identifies what's outdated, and automates safe updates while protecting product-specific content. Triggers on requests to sync with template, update template version, check for template drift, or when user asks "sync template", "update to v3", "template drift", "check template version".

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Allocate launch channels using the Owned / Rented / Borrowed (ORB) framework during PRD v0.9 Go-to-Market. Triggers on requests to pick launch channels, distribute the offer, build a channel portfolio, or when user asks "where do we launch?", "what channels?", "ORB", "owned vs rented vs borrowed", "channel allocation", "channel mix", "Corey Haines launch". Outputs GTM-* entries with Type=Channel, a channel-mix matrix, and a launch sequence.

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Define and prioritize features with strategic traceability during PRD v0.3 Commercial Model. Triggers on requests to define features, prioritize capabilities, scope MVP, map features to pricing tiers, identify parity vs. delta features, or when user asks "what features do we build?", "what's in MVP?", "which features matter?", "feature priority", "parity features", "what's our delta?". Consumes KPI- (Outcome Definition), BR- (Pricing Model, Moat), and CFD- (Market Moat Analysis) from v0.3. Outputs FEA- entries with strategic traceability and BR-FEA- governance rules. Feeds v0.4 User Journeys.

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Validates gate criteria before PRD lifecycle advancement by delegating to the readiness scoring pipeline (scripts/readiness.py). Returns a graduated PASS / WARN / BLOCK verdict with top blockers and their causal chain. Triggers before advancing from v0.X to v0.Y or explicit `/ghm-gate-check`.

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Map customer journeys from awareness to advocacy. Visualize touchpoints, identify drop-off points, analyze channel interactions, and optimize the end-to-end experience. Use when the user asks about customer journey, funnel mapping, touchpoint analysis, or experience optimization.

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Generate and maintain llms.txt files for AI discoverability. Scans repos to create curated content maps that help AI answer engines surface your project accurately. Implements the llms.txt specification from Answer.AI.

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Use when the user has a Xiaohongshu niche and needs to find, compare, and extract reusable content structures from low-follower high-performing posts, or diagnose why a post did or did not become a breakout using click rate, retention, and interaction signals. Trigger phrases: "找对标", "低粉爆款", "拆爆款", "内容骨架", "点击率", "停留时长", "互动率", "competitor pattern", "viral post structure". Do not use before the monetization direction is clear.

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Use when the user has an AI-generated Xiaohongshu draft and wants it to sound more personal, concrete, platform-appropriate, and stronger in hook, retention, and interaction value. Trigger phrases: "去 AI 味", "不像我", "合规检查", "改得像真人", "开头不抓人", "没停留", "humanize draft", "platform check". Do not use for initial positioning or topic generation.

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

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Cut AI tells from any writing. Must always apply.

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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.

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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'.

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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.

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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.

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

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Install and wire registry blocks and components into HyperFrames compositions. Use when running hyperframes add, installing a block or component, wiring an installed item into index.html, or working with hyperframes.json. Covers the add command, install locations, block sub-composition wiring, component snippet merging, registry discovery, and authoring a new block or component to contribute upstream (idea → scaffold → validate → PR).

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Strip AI writing tells from Rove's user-facing prose — README, the docs/ pages that sync to docs.rove.run, landing copy, and release notes. Use when the user says "unslop", "洗一下文案", "这读起来像 AI 写的", or after drafting any user-facing page. Adapted for this repo from cursor/plugins pstack/skills/unslop.

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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.

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Elixir is a functional language on the Erlang VM (BEAM) for concurrent, fault-tolerant and distributed systems. Use when someone asks to "write Elixir", "build a Phoenix app", "Phoenix LiveView", "GenServer", "supervision tree", "Ecto schema or changeset", "mix project", or needs lightweight processes, "let it crash" reliability and real-time web UIs.

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Add live chat and customer support with Crisp. Use when a user asks to add a chat widget, implement live customer support, set up a help desk, create a knowledge base, or add a chatbot to a website.

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Create compelling, personalized cover letters that help you stand out in job applications. Use when a user asks to write a cover letter, draft a job application letter, create a letter of interest, compose a motivation letter, or personalize an application for a specific company and role.

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You are an expert in Chi, the lightweight, idiomatic Go HTTP router built on `net/http`. You help developers build composable HTTP services using Chi's middleware stack, route groups, URL parameters, sub-routers, and context-based request scoping — providing Express-like ergonomics while staying 100% compatible with Go's standard library.

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Collect and manage product feedback with Canny. Use when a user asks to set up a feature request board, prioritize product feedback, build a public roadmap, or let users vote on features.

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