emerging-market-skills: Instructions file for Codex

AGENTS.md

emerging-market-skills AGENTS.md is an instructions file for Codex, OpenCode from Kaguara/emerging-market-skills. It costs 2,296 tokens per session, scanned A, original, MIT.

A set of software design rules for applications used on low-cost phones, unreliable mobile networks, and prepaid data plans in emerging markets. It treats limited memory, processing power, connectivity, and user budgets as core constraints.

In plain words
What is it for?
Use it when designing, coding, or reviewing mobile and web software intended for entry-level Android phones and intermittent 3G connections.
Why use it?
It helps developers avoid assuming fast internet, modern devices, unlimited storage, or affordable data.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md.

This is Kaguara/emerging-market-skills's own configuration. It tells Codex and OpenCode how to work on emerging-market-skills itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything emerging-market-skills configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Kaguara/emerging-market-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Kaguara/emerging-market-skills/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/Kaguara/emerging-market-skills

Made for: Codex, OpenCode.

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Per session 2,296 This file is loaded in full into every session.
When invoked 2,296 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.02296 $0.02296
Opus 5 $0.01148 $0.01148
Sonnet 5 $0.00459 $0.00459
Haiku 4.5 $0.00230 $0.00230

Measured 12d ago against content hash 608d14dae4c1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

emerging-market-skills AGENTS.md 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.

AGENTS.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Building for emerging markets

Drop this file at the root of your project. Every rule below is a constraint for software used on entry-level devices, over intermittent and expensive connections, by people whose first computer is the phone in their hand.

Full guidance, worked code, and runnable validators: https://github.com/Kaguara/emerging-market-skills

The design target

Unless told otherwise, assume tier C: an entry-level Android phone with 1–2GB of RAM shared with the OS, a CPU roughly a quarter as fast as a current flagship, storage permanently near full, an ageing battery, on congested 3G with frequent handover, paid for from a prepaid bundle bought in small increments.

The four constraints

  • Network — not slow, but intermittent, ambiguous, and dishonest. Requests that neither succeed nor fail. Connectivity flags reporting a live link that carries no traffic to your origin.
  • Device — memory and CPU that fall off cliffs rather than degrading smoothly. Your process is a candidate for termination whenever it backgrounds.
  • Cost — two meters running: yours per SMS, per API call, per token; theirs per megabyte, prepaid.
  • Interface — read in a language with longer words than English, sometimes by someone using a smartphone for the first time.

How to apply this

Severity means: critical — the product does not work for the target user. warning — measurable degradation. advisory — a better default.

When you flag something, cite the rule ID. When something is wrong and no rule covers it, say so and label it judgment rather than inventing a citation.

Emerging market review

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

Read the full file on GitHub · 172 lines

Changes

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.

  1. 12d ago First seen · 172 lines · 2,296 tokens per session scan A 608d14dae4c1

Subscribe to this mod's changes

emerging-market-skills AGENTS.md is an instructions file published in the GitHub repository Kaguara/emerging-market-skills (7 stars, last pushed 16d ago), licensed MIT. It adds 2,296 tokens to every session, about $0.0115 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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