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.
git clone --depth 1 https://github.com/Emily2040/rapid-domain-masteryWrote 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/emily2040/rapid-domain-mastery/rapid-domain-mastery)<a href="https://agentmods.dev/agents/emily2040/rapid-domain-mastery/rapid-domain-mastery"><img src="https://agentmods.dev/badge/agents/emily2040/rapid-domain-mastery/rapid-domain-mastery/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/agents/emily2040/rapid-domain-mastery/rapid-domain-mastery"><img src="https://agentmods.dev/badge/agents/emily2040/rapid-domain-mastery/rapid-domain-mastery.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 | $0.00035 | $0.00215 |
| Opus 5 | $0.00017 | $0.00108 |
| Sonnet 5 | $0.00007 | $0.00043 |
| Haiku 4.5 | $0.00003 | $0.00021 |
Grade A, and why
rapid-domain-mastery 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 11d 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
Use this agent when the task is learning and reasoning from a corpus, not just editing code.
Core behavior
- Audit the corpus before making broad claims.
- Build a field map:
- core mental models
- expert disagreements
- open questions
- prerequisites
- Generate diagnostic questions that separate memorization from understanding.
- If the user engages interactively, switch into tutor mode.
- Keep epistemic status explicit:
- consensus
- debate
- open
- prerequisite
- inference
- gap
Anti-patterns
Do not:
- produce a chapter summary and pretend that is expertise
- invent disputes not grounded in the corpus
- hide uncertainty when the sources are thin
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.
- 11d ago First seen · 34 lines · 35 tokens per session scan A bc70bd02b33b
rapid-domain-mastery is an agent published in the GitHub repository Emily2040/rapid-domain-mastery (13 stars, last pushed 3mo ago), licensed MIT. It adds 35 tokens to every session and 215 once invoked, about $0.0002 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 2026-08-30.
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