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 agentmods add agents/yosefhayim/launch-store/domaingit clone --depth 1 https://github.com/YosefHayim/launch-storeWrote 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/agents/yosefhayim/launch-store/domain)<a href="https://agentmods.dev/agents/yosefhayim/launch-store/domain"><img src="https://agentmods.dev/badge/agents/yosefhayim/launch-store/domain.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00407 |
| Opus 5 | $0.00000 | $0.00204 |
| Sonnet 5 | $0.00000 | $0.00081 |
| Haiku 4.5 | $0.00000 | $0.00041 |
Grade A, and why
domain 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 4d 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.
What it actually says
Domain Docs
How the engineering skills should consume this repo's domain documentation when exploring the
codebase. launch-store is single-context: one CONTEXT.md + docs/adr/ at the repo root.
Before exploring, read these
CONTEXT.mdat the repo root - what Launch is, how the build -> sign -> submit flow fits together, and ## Language (Launch-specific domain terms).TECH.mdat the repo root - the React Native / Expo / Apple / Google stack glossary (provisioning profile, AAB, keystore, track). Use these terms; do not drift to synonyms.docs/adr/- read any ADRs that touch the area you're about to work in (created lazily as decisions get resolved).
If a file doesn't exist, proceed silently - don't flag its absence or suggest creating it upfront.
File structure (single-context)
/
CONTEXT.md <- project + architecture + ## Language
TECH.md <- stack / ecosystem glossary
docs/adr/ <- architectural decision records (lazily created)
src/
Use the glossary's vocabulary
When your output names a domain concept (an issue title, a refactor proposal, a hypothesis, a test
name), use the term as defined in CONTEXT.md ## Language / TECH.md. The runtime source of truth for the
teaching copy is src/core/glossary.ts; the root docs are the human/agent-readable companion.
If the concept you need isn't in the glossary yet, that's a signal - either you're inventing language the project doesn't use (reconsider), or there's a real gap (note it).
Flag ADR conflicts
If your output contradicts an existing ADR, surface it explicitly rather than silently overriding:
Contradicts ADR-0003 (manual signing only) - but worth reopening because...
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.
- 4d ago First seen · 38 lines · 0 tokens per session scan A 5c5501c50243
domain is an agent published in the GitHub repository YosefHayim/launch-store (9 stars, last pushed 7d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 407 tokens. 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 2026-08-31.
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aso-compliance
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aso-keywords
Keyword research specialist. Analyzes keyword coverage, difficulty, volume, and placement across app store metadata fields. Platform-aware: handles iOS indexing rules (title + subtitle + keywords field) vs Android (title + short desc + full description NLP crawling).
aso-competitors
Competitor intelligence specialist. Compares keyword targeting, metadata strategy, visual approaches, and ratings across competitor apps. Identifies keyword gaps and differentiation opportunities.
aso-conversion
Conversion rate specialist. Evaluates the app store listing from a user psychology perspective. Analyzes first-impression elements, screenshot narrative, social proof signals, and persuasion techniques.
aso-metadata
Metadata optimization specialist. Validates character limits, scores field quality, checks keyword placement, and generates improved metadata variants. Balances keyword placement with conversion copywriting.
aso-reviews
Review analysis specialist. Performs sentiment classification, extracts keyword themes from reviews, analyzes rating distribution, and generates response strategy recommendations.