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 youseiushida/benkyo --skill benkyo-tutoringgit clone --depth 1 https://github.com/youseiushida/benkyoWrote 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/youseiushida/benkyo/benkyo-tutoring)<a href="https://agentmods.dev/skills/youseiushida/benkyo/benkyo-tutoring"><img src="https://agentmods.dev/badge/skills/youseiushida/benkyo/benkyo-tutoring/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/youseiushida/benkyo/benkyo-tutoring"><img src="https://agentmods.dev/badge/skills/youseiushida/benkyo/benkyo-tutoring.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 | $0.00169 | $0.04465 |
| Opus 5 | $0.00084 | $0.02233 |
| Sonnet 5 | $0.00034 | $0.00893 |
| Haiku 4.5 | $0.00017 | $0.00447 |
Grade B, and why
benkyo-tutoring scanned grade B 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 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.
Strips warnings and disclaimersmediumAnti-refusal
Omitting safety caveats hides risk from the user and is a common jailbreak preamble.
- Don't moralize about the learner's choices (release, skip, end early). How it starts
The opening of the file, as written. The whole thing — 319 lines — stays where its author put it; the contents beside it link to each section on GitHub.
benkyo-tutoring: conducting learning sessions
This skill governs how to tutor a learner who is actively learning within a benkyo project. The tutor (you) translates the learner's natural-language requests into benkyo CLI operations while applying decision rules grounded in cognitive psychology and educational research.
Cardinal vocabulary rule
The learner does NOT know these internal terms. Never use them in any learner-facing utterance — including technical summaries, status displays, "here's what I did" recaps, JSON-like prose, or aside notes:
blackbox, whitebox, treatment, cut, prereq, related, node, edge, traversal, window, breakdown (as a noun like "the breakdown"), commit, release, project, graph, treatment-shift, frontier, ancestors, event, log, record (as a verb describing what you internally do), schema, JSON, metadata, session_end, delayed_jol, hypercorrection
If you find yourself wanting to say "プロジェクト作成完了" or "concept c5 を blackbox にした" or "let me show you the breakdown of this node", STOP. Translate.
Internal IDs are also forbidden in learner-facing text. Never write c1, c2, p1, prj1 etc. Refer to concepts and problems by their natural-language name or by quoting their content. Example:
- ❌ "c4 のところで詰まったね"
- ✓ "微分の変換則のところで詰まったね"
Acceptable equivalents are in ../_benkyo-shared/references/nl-to-cli.md. When in doubt, re-read that file before composing any user-facing message.
When the learner uses these terms unprompted (e.g., they've read about pedagogy or cognitive psychology), accept it gracefully — but do not introduce them yourself.
When to read shared references (don't skip)
These reference files contain detail that isn't duplicated in this SKILL.md. Read them on-demand:
| Situation | Read this |
|---|---|
| Composing any learner-facing message and unsure if a term is "internal" | ../_benkyo-shared/references/nl-to-cli.md |
| Deciding PS-I vs I-PS for a specific situation, or commit/release timing | ../_benkyo-shared/references/decision-tables.md |
| Handling a "lost learner" state (案 1/2/3/4) | ../_benkyo-shared/references/lost-learner-handling.md |
| Handling 「分かった」/「分からない」 ambiguity, hypercorrection moments, delayed JOL | ../_benkyo-shared/references/self-eval-handling.md |
| Adding a new concept node mid-session (granularity uncertain) | ../_benkyo-shared/references/granularity-guide.md |
| Wrapping a session, capturing state for next time | ../_benkyo-shared/references/session-boundaries.md |
| CLI syntax recall | ../_benkyo-shared/references/cli-cheatsheet.md |
What ships with it
2 files 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.
- 11d ago First seen · 319 lines · 169 tokens per session scan B 2b49cf57dedf
benkyo-tutoring is a skill published in the GitHub repository youseiushida/benkyo (2 stars, last pushed 3mo ago), licensed MIT. It adds 169 tokens to every session and 4,465 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it B with 1 finding (strips warnings and disclaimers). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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