keyword-research
by Eronredkeyword-research is an ASO skill for discovering, evaluating, and prioritizing App Store keywords. Use it when you need a research workflow for seed expansion, competitor keyword analysis, and ranking opportunities. It helps turn rough app context into a prioritized keyword strategy instead of a generic brainstorm.
This skill scores 78/100, which means it is a solid directory candidate: users get a clearly triggered ASO keyword-research workflow with enough operational detail to be useful, though they should expect some gaps because the repository has no companion scripts, references, or install command. It is listable, but best framed as a focused text-first workflow rather than a fully packaged tool.
- Strong triggerability: the frontmatter names clear use cases such as discovering, evaluating, and prioritizing App Store keywords, plus explicit trigger phrases like "keyword research" and "search volume".
- Good operational structure: the skill lays out an initial assessment and phased research process, which reduces guesswork versus a generic prompt.
- Substantial workflow content: the body is relatively large with headings, constraints, and code fences, and it includes repo/file references for related skills like metadata-optimization and aso-audit.
- No install command or supporting files: there are no scripts, references, resources, or metadata extras, so adoption depends on the SKILL.md content alone.
- Evidence suggests a specialized ASO workflow: it is useful for App Store keyword strategy, but not a general keyword-research skill across platforms or SEO contexts.
Overview of keyword-research skill
keyword-research is an ASO-focused skill for finding, evaluating, and prioritizing App Store keywords with less guesswork than a generic prompt. It is best for people who need a keyword list they can actually act on: app marketers, founders, ASO specialists, and agents working from a rough product brief. The main job-to-be-done is to turn a few seed terms into a ranked keyword strategy that balances relevance, search demand, competition, and business intent.
What keyword-research is best for
Use the keyword-research skill when you need to answer questions like: what should this app target first, which terms are worth indexing, and which competitors’ keywords are realistic opportunities. It is especially useful when the app category is crowded and you need a decision process, not just a brainstorm.
Why this skill is more useful than a plain prompt
The keyword-research guide is built around an actual research workflow: it starts from app context, asks for the App ID and country, expands seeds, then evaluates opportunities. That structure helps avoid the common failure mode of producing attractive keywords that are irrelevant, unrankable, or wrong for the target market.
When keyword-research is the right fit
This keyword-research for Keyword Research is a good fit if you want discovery and prioritization. It is not the right first step if you already know the exact metadata copy you want to write, or if you only need to check current ranking performance without doing new research.
How to Use keyword-research skill
Install keyword-research in your workflow
Use keyword-research install through your normal skills setup flow, then confirm the skill directory is available in your agent’s working context. In this repo, the active skill lives at skills/keyword-research, and SKILL.md is the first file to read. Because there are no helper scripts or reference folders, the skill is meant to be driven directly from the markdown instructions rather than from a larger toolchain.
Give the skill the inputs it needs
The skill works best when you provide five things up front: App ID, target country, 3-5 seed keywords, app category or positioning, and the goal of the research. A weak request sounds like “find keywords for my app.” A stronger keyword-research usage prompt sounds like: “Research keyword opportunities for App ID 123456789 in US. Seed terms: habit tracker, planner, focus timer. Goal: downloads for new users. Competitors: Structured, TickTick, Todoist.”
Read the files in the right order
Start with SKILL.md to understand the process, then inspect any project context file named app-marketing-context.md if your workspace includes one. The key advantage of this skill is the sequencing: initial assessment, seed expansion, then keyword evaluation. If you skip the assessment step, you usually end up with a longer list but a weaker strategy.
Use a prompt that matches the research phase
For discovery, ask for breadth: “Expand these seeds into candidate keywords and group them by intent.” For prioritization, ask for ranking: “Score these keywords by relevance, likely demand, and competitiveness, then recommend the top 10.” For competitor analysis, ask for overlap and gaps: “Compare my app to these 5 competitors and identify keywords they rank for that I do not.”
keyword-research skill FAQ
Do I need ASO experience to use keyword-research?
No. The keyword-research skill is beginner-friendly because it asks for concrete inputs and follows a research sequence. You do not need to know ranking theory before using it, but better app context and cleaner seed terms will improve the output.
How is this different from an ordinary prompt?
An ordinary prompt can brainstorm keywords, but keyword-research adds a repeatable process: assess the app, expand from seeds, compare competitors, and prioritize by intent. That makes it more reliable when you need a decision-ready shortlist instead of a raw idea dump.
When should I not use keyword-research?
Do not use keyword-research if your task is mainly writing metadata, changing screenshots, or checking existing rankings without discovery work. In those cases, a metadata-focused or audit-focused skill will be a better match than a keyword research workflow.
What is the main boundary of the skill?
The skill is optimized for App Store keyword strategy, not generic SEO or web search optimization. If your target is a website, YouTube channel, or Google Play-only workflow, the assumptions in keyword-research may not transfer cleanly.
How to Improve keyword-research skill
Start with stronger seed keywords
The biggest quality jump comes from better seeds. Instead of broad terms like “fitness” or “productivity,” give the skill functional phrases tied to user intent, such as “meal planner,” “screen time blocker,” or “AI note taker.” Better seeds produce better expansion paths and fewer off-target suggestions.
Add context that changes keyword value
Mention the app’s audience, use case, and monetization goal. “Budgeting app for students” and “budgeting app for freelancers” can lead to very different keyword-research results because relevance and conversion intent are not the same. If you have competitors, include them early so the skill can compare real market alternatives instead of guessing.
Ask for output in a usable format
Do not just ask for “best keywords.” Ask for a ranked list with reasons, intent labels, and notes on competition or risk. A useful follow-up is: “Return the top 20 keywords, grouped into primary targets, secondary targets, and low-priority tests.” That makes the output easier to feed into metadata work.
Iterate after the first pass
Use the first result to tighten the next prompt. If the list is too broad, narrow by audience or feature. If the list is too generic, add competitor names or a more specific country. If the list feels too aggressive, ask for a conservative pass focused on realistic ranking opportunities rather than high-volume terms.