Atomic Agent is a local-first AI agent that runs its control loop and state on a user's machine while using local or cloud models. It drives browsers, edits files, runs approved commands, remembers context, schedules follow-ups, and connects to external tools, with the catalogue providing skills for its use.
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 AtomicBot-ai/atomic-agent --skill currencygit clone --depth 1 https://github.com/AtomicBot-ai/atomic-agentWrote 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/atomicbot-ai/atomic-agent/currency)<a href="https://agentmods.dev/skills/atomicbot-ai/atomic-agent/currency"><img src="https://agentmods.dev/badge/skills/atomicbot-ai/atomic-agent/currency/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/atomicbot-ai/atomic-agent/currency"><img src="https://agentmods.dev/badge/skills/atomicbot-ai/atomic-agent/currency.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 23 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 42 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 48 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 54 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00033 | $0.00851 |
| Opus 5.5 | $0.00013 | $0.00340 |
| Sonnet 5.5 | $0.00007 | $0.00170 |
| Haiku 4.5 | $0.00003 | $0.00085 |
Grade A, and why
currency scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
[{ "tool": "os.shell.run", "args": { "cmd": "curl", "args": ["-fsS", "--max-time", "25", "https://api.frankfurter.dev/v1/latest?base=USD&symbols=EUR&amount=100"] } }] How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
currency
Fetch exchange rates and convert money amounts through the free, key-less
Frankfurter API (ECB-sourced fiat rates, updated
daily ~16:00 CET). Prefer os.http.request GET; if the host allowlist is
not null, it must include api.frankfurter.dev.
Fiat only — no crypto, no precious metals on v1. Rates refresh on business days, so weekend/holiday requests return the most recent business-day rate.
Endpoints (v1, stable)
Base URL: https://api.frankfurter.dev/v1
| Goal | URL |
|---|---|
| Latest, EUR base, all currencies | /latest |
| Latest with base + targets | /latest?base=USD&symbols=EUR,GBP |
| Convert an amount | /latest?base=USD&symbols=EUR&amount=100 |
| Historical (single day) | /2024-01-15?base=USD&symbols=EUR |
| Time series (date range) | /2024-01-01..2024-01-31?base=USD&symbols=EUR |
| Supported currencies | /currencies |
symbols is a comma-separated list of ISO 4217 codes. amount multiplies the
returned rate, so amount=100&base=USD&symbols=EUR gives "100 USD in EUR".
Calling convention
Latest rate with os.http.request:
[{ "tool": "os.http.request", "args": { "method": "GET", "url": "https://api.frankfurter.dev/v1/latest?base=USD&symbols=EUR,GBP" } }]
Convert 250 USD to JPY:
[{ "tool": "os.http.request", "args": { "method": "GET", "url": "https://api.frankfurter.dev/v1/latest?base=USD&symbols=JPY&amount=250" } }]
Fallback if os.http.request is unavailable or the host is not allowlisted:
[{ "tool": "os.shell.run", "args": { "cmd": "curl", "args": ["-fsS", "--max-time", "25", "https://api.frankfurter.dev/v1/latest?base=USD&symbols=EUR&amount=100"] } }]
Response shape
{ "amount": 100.0, "base": "USD", "date": "2026-05-29", "rates": { "EUR": 92.13 } }
rates[<symbol>] already reflects amount. Always report the date so the user
knows how fresh the quote is.
When to use
- "What's the USD/EUR rate?", "convert 50 GBP to PLN", "rate of X in Y".
- Historical FX on a given date, or a rate trend over a period.
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.
- 1mo ago First seen · 85 lines · 33 tokens per session scan A c3e6228139ca
currency is a skill published in the GitHub repository AtomicBot-ai/atomic-agent (3,431 stars, last pushed yesterday), licensed MIT. It adds 33 tokens to every session and 851 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
financial-analysis
Financial figures done carefully: periods and fiscal calendars, units and currencies, reconciliation, magnitude sanity checks, sourced assumptions. Use for statements, budgets, pricing, and diligence numbers.
harness-init-runner
Initialize a lightweight repo-local Node.js harness (harness/ + .harness/) WITHOUT AIOS dependency. Use ONLY when you need a standalone, portable harness. If AIOS is installed, use aios-long-running-harness instead — it has rex Command hosting, ContextDB integration, and checkpoint recovery.
hatch3r-cost-tracking
Tracks token usage and estimate costs for agent sessions. Use when monitoring spend, approaching budget limits, or generating cost reports.
manage-llm-server
Inspect and control the local LLM server(s) via llama-launcher — list profiles, see what's running, switch models, tail logs. Use when the user wants to know what model is loaded, change models, start/stop or restart the server, or troubleshoot a stuck load.
release-llama-launcher
Cuts a llama-launcher release: checks the release gate with go run ./cmd/release status, drafts the notes with release-notes-llama-launcher, proposes the version and has the owner confirm it, makes the two local release commits with prepare, then — after a dry run and one explicit confirmation — runs publish, which…
finance
Budget planning, cash flow management, financial modeling, reporting, tax strategy, investment analysis, and fundraising skills. Spreadsheet models, P&L, balance sheets. Triggers on: finance, budget, cash flow, financial model, P&L, balance sheet, fundraising, valuation, accounting.