# Asc Keywords > Generate localized ASC keyword-field recommendations for iOS apps. Use when the user asks for App Store Connect keywords, ASO keyword research, localized ASC keyword sets, or a 100-character keyword field. Focus only on the hidden Keywords field, not title, subtitle, screenshots, descriptions, or other ASC metadata. - **Type:** Skill - **Install:** `agentstack add skill-raydeveloperf-app-store-connect-release-kit-asc-keywords` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [raydeveloperF](https://agentstack.voostack.com/s/raydeveloperf) - **Installs:** 0 - **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [raydeveloperF](https://github.com/raydeveloperF) - **Source:** https://github.com/raydeveloperF/App-Store-Connect-release-kit/tree/main/skills/asc-keywords ## Install ```sh agentstack add skill-raydeveloperf-app-store-connect-release-kit-asc-keywords ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # ASC Keywords Use this skill to produce one or more localized App Store Connect `Keywords` fields. The deliverable is keyword-only ASO output: no subtitle, no title rewrite, no screenshot copy, no marketing description. ## Project Context First Before keyword research, gather enough context to understand the current app. Do not jump straight from a category label to final keywords. If a local project or workspace is available, inspect the relevant app files first, such as product docs, README, app entry points, feature screens, localization files, existing App Store metadata, or marketing copy. Keep the pass lightweight and read-only unless the user asks for edits. Build a short working brief before generating candidates: - App name, category, and target platforms. - Core user job and the 3-5 strongest implemented features. - Target audience, usage scenario, and likely search intent. - Existing title/subtitle/metadata words that must not be duplicated in `Keywords`. - Localization languages and any locale-specific product differences. - Competitive posture: new indie app, niche app, or already established app. If the project context is missing or too thin, ask focused questions or request the minimum files/evidence needed. It is acceptable to produce a starter keyword set only after labeling it as context-limited and pending App Store validation. ## Required Inputs The only input that cannot be inferred: **target locales** (e.g. `en-US`, `zh-Hans`). If target locales are missing and were not provided by the caller, ask once and stop. Everything else — app category, core user job, seed words — infer from the product brief or project files. Do not ask the user for these. ## Candidate Generation Build candidates from the product brief and project evidence: 1. Extract core function words and feature names from the product brief. 2. Add locale-native synonyms for those functions and common user search intent words. 3. Pull any competitor vocabulary the user or brief already mentions. 4. Label the result as "starter set — validate with on-device App Store search before shipping" when no live autocomplete evidence is available. ## Saturation Screening For each candidate or autocomplete phrase, classify the competitive shape: - `avoid`: top results are dominated by large brands, platform giants, or exact-brand intent. - `keep`: results include small or indie apps, lower-review apps, or mixed-quality competitors. - `priority`: a relevant long-tail phrase has weak-looking competition and direct product fit. - `unclear`: insufficient evidence; keep only if it is semantically strong and space-efficient. Bias toward long-tail component words that can combine into multiple useful phrases. For a new indie app, do not spend scarce characters on giant head terms unless they are short, essential, and highly reusable. ## Keyword Field Rules Build each localized App Store Connect keyword field under the 100-character limit. - Use comma-separated tokens with no spaces: `word1,word2,word3`. - Count physical characters, including commas. Keep each final string at `<= 100`. - Do not repeat tokens already present in the provided app name/title/subtitle. - Do not repeat tokens inside the keyword field. - Split English phrases into component words when that saves space, such as `home,workout` rather than `home workout`. - Remove filler and platform words: `app`, `free`, `iphone`, `ipad`, `ios`, `apple`. - Avoid English plural duplicates when the singular is enough. - Avoid competitor brand names, celebrity names, and trademarked terms unless explicitly requested. - For languages without spaces, such as Chinese or Japanese, use natural searchable words/short phrases as tokens; do not force single-character splitting. - Preserve meaningful accents or locale-specific spelling when users search that way. ## Output Format Return a compact table per locale: | Locale | Keywords | Count | Notes | | --- | --- | ---: | --- | | en-US | `journal,diary,mood,habit,photo,calendar` | 40 | starter set; validate autocomplete | Then include: - `Priority phrases`: 5-10 phrase combinations the token set is intended to cover. - `Removed`: duplicates, giant-brand terms, filler/platform words, and weak terms. - `Manual validation checklist`: exact App Store searches the user should run before shipping. If final evidence is weak, say so plainly. Do not pretend the set is production-grade when it was built without App Store autocomplete or competitor-result checks. ## Quality Bar A good final answer: - Produces a ready-to-paste keyword string for every requested locale. - Stays under 100 characters per locale. - Explains tradeoffs briefly. - Uses locale-native search language. - Avoids title/subtitle recommendations unless the user separately asks for them. - Writes the final Markdown output, grouped by language, to a file: use the output path provided by the caller if one was given, otherwise write to `asc-keywords.md` in the current working directory. Confirm the absolute path in the completion summary. ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [raydeveloperF](https://github.com/raydeveloperF) - **Source:** [raydeveloperF/App-Store-Connect-release-kit](https://github.com/raydeveloperF/App-Store-Connect-release-kit) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-raydeveloperf-app-store-connect-release-kit-asc-keywords - Seller: https://agentstack.voostack.com/s/raydeveloperf - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.