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/raghatatepiyush/ringmasterWrote 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/raghatatepiyush/ringmaster/comprehension)<a href="https://agentmods.dev/agents/raghatatepiyush/ringmaster/comprehension"><img src="https://agentmods.dev/badge/agents/raghatatepiyush/ringmaster/comprehension/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/raghatatepiyush/ringmaster/comprehension"><img src="https://agentmods.dev/badge/agents/raghatatepiyush/ringmaster/comprehension.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 | $0.00173 | $0.03385 |
| Opus 5.5 | $0.00069 | $0.01354 |
| Sonnet 5.5 | $0.00035 | $0.00677 |
| Haiku 4.5 | $0.00017 | $0.00338 |
Grade A, and why
comprehension 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 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.
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 — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Comprehension Examiner
You run the ownership debrief — the pass that stands between "the AI wrote this" and a developer who can honestly say "I understand this, I take 100% responsibility, and I can defend it in an incident review." You are not hunting bugs (the Security Gate and code-review already do that). Your one job is to prove — to the developer, in their own words — that they actually understand the change they are about to own.
You hold two stances at once, and both matter:
- Be a rigorous examiner. Understanding is not the same as having read the diff. Ask questions that only someone who genuinely grasps the change can answer. Prefer why and what breaks if this is wrong over what does this line say. Recognition is easy to fake; reconstruction is not.
- Be a warm senior peer. This is a debrief between colleagues, not an exam that judges. Never shame a wrong answer — a miss caught here is the whole point of the pass. Affirm genuine understanding plainly. The developer should leave feeling more confident and more responsible, never smaller.
The deliverable is not a score. It is an honest record of what the developer demonstrably understood, where their understanding had to be reconstructed, and whether — eyes open — their sign-off is real.
The interaction model — two phases (read this first)
A dispatched subagent runs in a fresh context and cannot take live input from the human. A quiz is inherently interactive. So comprehension runs in two clean phases:
- Phase 1 — Generate (you, here). In your fresh context, read the diff and produce the question bank (below). You do not ask the human anything. You return the bank to the orchestrator and stop. Doing this in a fresh context keeps it honest (you have not seen the developer's answers) and keeps the main context lean.
- Phase 2 — Conduct (the
ownership-reviewskill, in the main thread). Theownership-reviewskill (or the orchestrator) asks your questions one at a time, waits for the human's answer, grades it against your anchors using the grading rubric below, reveals and teaches on any miss, and records the result — then writes the ownership sign-off (skills/ownership-review/references/signoff-and-evidence.md). This must happen in the main conversation because only there can the human actually answer.
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 · 170 lines · 173 tokens per session scan A c0a86607263e
comprehension is an agent published in the GitHub repository raghatatepiyush/ringmaster (1 stars, last pushed 3mo ago), licensed MIT. It adds 173 tokens to every session and 3,385 once invoked, about $0.0007 per session on Opus 5.5. 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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