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 agentmods add skills/m98/fluent/fluent-vocabnpx skills add m98/fluent --skill fluent-vocabgit clone --depth 1 https://github.com/m98/fluentWrote 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/m98/fluent/fluent-vocab)<a href="https://agentmods.dev/skills/m98/fluent/fluent-vocab"><img src="https://agentmods.dev/badge/skills/m98/fluent/fluent-vocab.svg" alt="Measured on agentmods" 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 | $0.00073 | $0.01495 |
| Opus 5 | $0.00036 | $0.00747 |
| Sonnet 5 | $0.00015 | $0.00299 |
| Haiku 4.5 | $0.00007 | $0.00150 |
Grade A, and why
fluent-vocab scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vocabulary Drill Session
Overview
Flashcard-style vocabulary practice using spaced repetition. One word at a time, immediate feedback, DB update at the end. Interleaves three modes (recognition, production, cloze) to force active recall rather than passive re-reading.
When to Use
Trigger this skill only when the learner types /fluent-vocab. The skill is gated with disable-model-invocation: true — a false-positive auto-trigger would launch a 15-min interactive session and mutate 6 JSON databases. Not worth the risk.
Skip this skill if no vocabulary items are due and no new words are queued — offer /fluent-review or /fluent-learn instead.
Instructions
1. Load vocabulary data
python3 "${CLAUDE_PLUGIN_ROOT:-${CLAUDE_PROJECT_DIR:-.}}/.claude/hooks/read-db.py"
If the helper is unavailable, resolve <data_dir> via fluent_paths.data_dir() then read:
<data_dir>/spaced-repetition.json<data_dir>/mistakes-db.json<data_dir>/mastery-db.json<data_dir>/learner-profile.json(for target_language, name, level)
If any are missing, direct the learner to /fluent-setup and stop.
2. Select words
Priority order:
- Items in
spaced-repetition.review_queue.todaywithitem_type == "vocabulary". - Words from
mistakes-db.jsonwherecategory == "vocabulary"andmastery_level <= 2. - New high-frequency words matching
learner-profile.focus_areas.
Limit: spaced-repetition.daily_limits.review_items_per_day (default 20).
3. Present one word at a time
Rotate the three modes so the session is not monotonous.
Recognition (target_language → native):
## Word {N}/{total}
**{target_language}:** {word}
**Context:** {example_sentence}
**What does it mean in {native_language}?**
**Type your answer:**
Production (native → target_language):
## Word {N}/{total}
**{native_language}:** {word}
**Use it in a sentence (optional).**
**How do you say this in {target_language}?**
**Type your 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.
- 5d ago First seen · 204 lines · 73 tokens per session scan A ea3f0260312b
fluent-vocab is a skill published in the GitHub repository m98/fluent (387 stars, last pushed 2mo ago), licensed MIT. It adds 73 tokens to every session and 1,495 once invoked, about $0.0004 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.
Other skills, from other repositories
hr-onboarding
A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".
book-mirror
Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis. Each chapter is preserved in detail (The Chapter) and mirrored back to the reader's actual life (The Mirror) using brain context. The mirror observes and resonates — a friend pointing out parallels, NOT a consultant rearranging the reader's…
miniapp
Build a tiny interactive HTML playground only when someone asks to see, play with, or step through a mechanism.
eli5
Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.
deck-course-module
暖纸背景 + Playfair, 左侧学习目标常驻, 含 MCQ 自测页.
best-practices
Searchable knowledge base of 152+ programming best practices across 30+ languages and frameworks. BM25-powered search over curated resources from industry leaders (Google, Airbnb, Uber, Mozilla, Shopify, OWASP).