Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add MartinPuli/createAnApp --skill app-market-discoverygit clone --depth 1 https://github.com/MartinPuli/createAnAppWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/martinpuli/createanapp/app-market-discovery)<a href="https://agentmods.dev/skills/martinpuli/createanapp/app-market-discovery"><img src="https://agentmods.dev/badge/skills/martinpuli/createanapp/app-market-discovery/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/martinpuli/createanapp/app-market-discovery"><img src="https://agentmods.dev/badge/skills/martinpuli/createanapp/app-market-discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00084 | $0.00792 |
| Opus 5 | $0.00042 | $0.00396 |
| Sonnet 5 | $0.00017 | $0.00158 |
| Haiku 4.5 | $0.00008 | $0.00079 |
Grade A, and why
app-market-discovery scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
App Market Discovery
Search broadly enough to avoid anchoring on the first plausible idea. Deliver ranked opportunity hypotheses for later validation; do not call them validated.
Define the search mandate
Record:
- target Apple platforms, devices, territories, and languages;
- consumer, prosumer, or business preference;
- budget, deadline, team, and desired operator autonomy;
- acceptable acquisition and monetization models;
- whether interviews, sales, regulated review, moderation, physical service, or marketplaces are allowed;
- capabilities or risks the user explicitly excludes.
If constraints are missing, make reversible assumptions and label them. Do not narrow the world to categories already mentioned in the conversation.
Build a diverse opportunity universe
Generate candidates across unrelated jobs and industries. Look for:
- expensive, frequent, urgent, error-prone, or emotionally important work;
- underserved workflows hidden inside generic tools, paper, spreadsheets, desktop-only software, or fragmented services;
- changes in Apple hardware, frameworks, regulation, demographics, or business behavior;
- markets with reachable buyers and observable purchase intent;
- jobs where camera, microphone, location, offline work, Pencil, sensors, Shortcuts/App Intents, on-device processing, or Apple ecosystem continuity materially improve the outcome.
Exclude obvious clones, generic AI wrappers, repackaged websites, speculative network-effect markets without a liquidity plan, and ideas whose service burden violates the mandate.
Research the market landscape
Use current direct evidence:
- App Store queries by territory, ratings, review recency, screenshots, pricing, IAP/subscriptions, and update cadence;
- competitor sites, help centers, changelogs, public pricing, and positioning;
- search demand, forums, professional communities, complaints, procurement pages, and job posts;
- credible industry, demographic, and platform sources;
- current Apple features that create, commoditize, or eliminate an advantage;
- distribution channels where the buyer can actually be reached.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 80 lines · 84 tokens per session scan A e98a628e9cc3
app-market-discovery is a skill published in the GitHub repository MartinPuli/createAnApp (14 stars, last pushed 20d ago), licensed MIT. It adds 84 tokens to every session and 792 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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