Total 46,228 skills
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Launch an isolated Claude reviewer for the current branch, a specific commit, or uncommitted changes. Uses Claude's agent runtime with worktree isolation so the review has an independent read-only view of the code before findings are reported back.
Scan a Cargo workspace or package monorepo and refresh per-member `CLAUDE.md` files plus a thin root `CLAUDE.md`. User-only maintenance workflow for keeping workspace-local AI context accurate after refactors, member additions, export changes, or major architectural shifts.
Systematic debugging for ADK agents — trace reading, log analysis, common failure diagnosis, and the debug loop.
Complete FBA preparation guide. Product labeling, packaging requirements, shipment planning, and compliance with Amazon's fulfillment center requirements. Avoid common rejection reasons.
Amazon sales volume estimator for sellers and product researchers. Estimate monthly sales and revenue from BSR (Best Seller Rank), ASIN, or keyword. Three modes: (A) BSR Calculator — input BSR + marketplace + price + category to get instant sales estimate, (B) ASIN Lookup — input ASIN to auto-fetch data and estimate sales, (C) Keyword Market Analysis — input keyword to analyze total market size and competition. Works on 12 Amazon marketplaces. No API key required. Use when: (1) estimating how many units a product sells per month, (2) sizing a market or niche opportunity, (3) analyzing competitor sales performance, (4) comparing sales across price points, (5) identifying top sellers vs long-tail distribution.
Plan and optimize Amazon Sponsored Display campaigns. Audience targeting, product targeting, retargeting strategy, and creative optimization for awareness and conversion.
Amazon keyword research and market opportunity analysis for sellers. Retrieve autocomplete suggestions (long-tail keywords), analyze competitor landscape, and assess market opportunity for any keyword on 12 Amazon marketplaces (US/UK/DE/FR/IT/ES/JP/CA/AU/IN/MX/BR). No API key required. Make sure to use this skill whenever the user mentions Amazon product research, finding products to sell on Amazon, Amazon keyword ideas, niche analysis, competition analysis for Amazon, market opportunity on Amazon, comparing Amazon keywords, evaluating whether a product is worth selling, Amazon autocomplete data, seasonal demand for Amazon products, or anything related to researching what to sell on Amazon — even if they don't explicitly say 'keyword research'. Also trigger when the user asks vague questions like 'is this a good product to sell?', 'what's the competition like for X on Amazon?', 'should I sell X or Y?', or 'what are people searching for on Amazon?'.
Ultra-lightweight channel for feature workflows: No need to write design docs, checklists, or conduct phased reviews. Let AI write code directly as it normally would, but before it starts, tell it where the CodeStable knowledge base in the project is and how to search it. This way, the code it writes will have fewer pitfalls and be more consistent with project conventions. Trigger scenarios: Users say "fast mode", "fastforward", "skip all those steps", "just start coding", "help me make xxx" and the requirement is too small to go through the design process.
Discussion entry when ideas are still vague — first conduct triage through 1-2 rounds of dialogue to determine which downstream process this discussion should eventually go to: if the idea is clear enough, proceed directly to feature-design; if the direction of a small requirement is set, continue the discussion within the feature and document it in `{slug}-brainstorm.md`; if a large requirement cannot fit into a single feature, hand it over to roadmap for decomposition. The role of AI is a thinking partner, not a recorder — dig out the real problem the user wants to solve, proactively evaluate when the user brings a solution, and propose alternative directions when necessary. Trigger scenarios: when the user says "I have an idea that's not clear yet", "Let's brainstorm first", "I want to do something but it's still vague", "Let's talk about this area", "The function direction is still undecided", or when the user comes with a specific solution but wants to hear other ideas first. Bugs (go to issue) and refactoring (go to refactor) are not handled here.
Issue Workflow Stage 1 — Convert the user's problem into a reproducible, traceable {slug}-report.md through conversation. The AI only asks "what you saw, how to reproduce it, what should happen" here, and does not guess the root cause for the user (that's Stage 2's responsibility). Meanwhile, this stage is the only official decision point for choosing between the fast track and standard path: Based on the user's description, first review the relevant code; if the root cause can be identified at a glance and the required changes are minor, directly inform the user to take the fast track. Trigger scenarios: The user says "file an issue", "record this bug", "I found a problem". This is the starting point of the issue workflow with no pre-dependencies.
Ultra-lightweight channel for refactor processes - used when changes are clearly too small to go through the full scan → design → apply three-stage workflow. AI directly identifies 1-3 low-risk optimization points, confirms with the user once, modifies in-place using classic methods, and validates itself by running tests. No scan checklist, no design documentation, no multi-step human verification required. Trigger scenarios: User says "quick refactor", "small refactor", "simply optimize XX function", "modify directly", "skip the extra steps", and the scope of changes is clearly localized to a single function / single component with test coverage for self-validation.
When developing new features, follow this sub-process — take the vague idea of "add X capability" through to the acceptance closure, with solution documents archived so that both AI and users can later check the original thinking and decision rationale. Trigger scenarios are focused on adding new capabilities ("develop new feature", "add X", "implement XX"), and do not handle bugs in existing code. This skill only acts as a router, deciding which sub-skill to trigger next among brainstorm / design / fastforward / implement / acceptance based on existing artifacts.