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 ashermahonin/agentic-skills --skill platform-detectorgit clone --depth 1 https://github.com/ashermahonin/agentic-skillsWrote 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/ashermahonin/agentic-skills/platform-detector)<a href="https://agentmods.dev/skills/ashermahonin/agentic-skills/platform-detector"><img src="https://agentmods.dev/badge/skills/ashermahonin/agentic-skills/platform-detector.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 5.1 | $0.00070 | $0.00746 |
| Opus 5 | $0.00035 | $0.00373 |
| Sonnet 5 | $0.00014 | $0.00149 |
| Haiku 4.5 | $0.00007 | $0.00075 |
Grade A, and why
platform-detector 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 7d 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Platform Detector
Purpose
Translate a fuzzy product idea or an unfamiliar repository into a concrete target-platform matrix the rest of the skill chain can plan against. Without this, security, testing, performance, accessibility, and store-policy choices drift.
Inputs
- Read
references/platform-matrix.md. - Collect inputs from
init-project: stack fingerprint, user intent, deployment markers. - List the explicit platforms named by the user. If none were named, derive candidates from fingerprint markers and ask the user to confirm before locking in.
- For each candidate platform, name the store/distribution policy that applies (App Store, Google Play, Microsoft Store, Steam, web, internal enterprise, console SDK, package registry).
Decision process
- Build the platform matrix: rows are platforms; columns are runtime, distribution channel, accessibility baseline, performance budget, security track, testing matrix, telemetry constraints.
- Mark which cells are unknown and would benefit from Context7 MCP lookups (current SDK version, store policy revision, browser support floor, OS version coverage).
- For each platform, pin the security track: web/API/backend →
security-owasp-web; native iOS/Android →security-mobile-masvsplus backend/APIsecurity-owasp-webwhen applicable; LLM feature →security-owasp-llm; agentic surface →security-owasp-agentic; game → cheat-surface review plus dependency CVE checks. - Set a minimum testing matrix: e.g., web → 2 browser engines + 1 mobile viewport; iOS → 2 device sizes + dark mode + accessibility audit; Android → 2 API levels + at least one form factor.
- Surface conflicts: platforms whose budgets, policies, or stores disagree (for example, an iOS feature blocked by App Store rules but used freely on web).
- Hand the matrix to
architecture-reviewandrequirements-qualityso non-functional requirements pick it up automatically.
Decision boundaries
- Use Context7 MCP whenever current store policy, browser support, OS version table, or platform SDK behavior changes the answer.
- Keep a decision trace: candidate platforms, why included or excluded, store-policy risks, accessibility floor, security track per platform.
- Escalate before locking in a platform whose store policy or certification path could block release.
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.
- 7d ago First seen · 56 lines · 70 tokens per session scan A 209630025ce9
platform-detector is a skill published in the GitHub repository ashermahonin/agentic-skills (10 stars, last pushed 14d ago), licensed MIT. It adds 70 tokens to every session and 746 once invoked, about $0.0003 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 2026-08-31.
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