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 Kaguara/emerging-market-skills --skill emerging-market-reviewgit clone --depth 1 https://github.com/Kaguara/emerging-market-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/kaguara/emerging-market-skills/emerging-market-review)<a href="https://agentmods.dev/skills/kaguara/emerging-market-skills/emerging-market-review"><img src="https://agentmods.dev/badge/skills/kaguara/emerging-market-skills/emerging-market-review/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/kaguara/emerging-market-skills/emerging-market-review"><img src="https://agentmods.dev/badge/skills/kaguara/emerging-market-skills/emerging-market-review.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 | $0.00105 | $0.01796 |
| Opus 5 | $0.00053 | $0.00898 |
| Sonnet 5 | $0.00021 | $0.00359 |
| Haiku 4.5 | $0.00011 | $0.00180 |
Grade A, and why
emerging-market-review 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 12d 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Emerging market review
What this skill does
This is the router. It establishes who the product is for, applies the specialist skills that are relevant, and returns findings ranked by what breaks the product for the target user.
Use it when the question is broad ("will this work?"). Go straight to a specialist skill when the question is narrow ("what should our bundle budget be?").
Hard rules
| ID | Rule | Severity |
|---|---|---|
| REVIEW-001 | Establish the target market, device tier, and network profile before reviewing. | critical |
| REVIEW-002 | Every finding cites a rule ID, or is labelled as unsourced judgment. | critical |
| REVIEW-003 | Locate every finding in the artifact before reporting it. | critical |
| REVIEW-004 | Rank findings by user impact at the target tier, not by ease of fix. | warning |
| REVIEW-005 | State what was not checked. | warning |
Full detection criteria and remedies in rules.yml.
Step 1 — establish the target
Do not skip this. Every threshold in every other skill depends on it, and a review conducted without it produces advice that is true of software generally and useful to nobody in particular.
Ask, or state an assumption and continue:
- Market or markets. Prices, network conditions, languages, and payment rails all differ. "Emerging markets" is not a market.
- Device tier. A, B, C, or D from
docs/EVIDENCE.md. Default to C unless told otherwise. - Network profile. Congested 3G with frequent handover is the default assumption.
- Platform. Android, web, iOS, USSD, SMS — this decides which rules apply.
- Stage. A spec can be redirected; a shipped product needs findings ordered by what is worth changing now.
Write the assumption into the report. It is what makes the findings checkable.
Step 2 — dispatch
Load the specialist skills that apply. Most reviews need three or four, not all six.
| If the artifact involves | Load |
|---|---|
| Any network call, sync, retry, or offline behaviour | network-resilience |
| Dependencies, assets, build config, install or download size | payload-budgets |
| Lists, feeds, client-side computation, background work, memory | low-end-device-performance |
| SMS, push, USSD, WhatsApp, third-party APIs, AI or inference calls | integration-cost-modeling |
| Any user-facing string, layout, form, or icon | localization-and-literacy-ux |
| Signup, login, OTP, KYC, sessions, account recovery | identity-and-onboarding |
What ships with it
1 file 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.
- 12d ago First seen · 164 lines · 105 tokens per session scan A 2fdce25f3ad8
emerging-market-review is a skill published in the GitHub repository Kaguara/emerging-market-skills (7 stars, last pushed 17d ago), licensed MIT. It adds 105 tokens to every session and 1,796 once invoked, about $0.0005 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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