french-tutor

french-tutor is a skill for Claude Code, Codex from whateverforever/maxs-claude-skills. It costs 132 tokens per session (3,283 once invoked), scanned A, original, MIT.

An interactive French translation tutor for learners who understand advanced French but want to improve producing it. It gives English or German sentences to translate into French, then corrects answers and tracks mistakes.

In plain words
What is it for?
Use it for five-sentence practice batches, correction of French translations, mistake tracking, difficulty adjustment, and targeted retries.
Why use it?
It provides repeated sentence-writing practice with feedback instead of only testing reading or listening. Mastery retries bring recurring mistakes back for another attempt.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Not installable: its command points at a path on the author’s own machine, so it runs nowhere else. The line is /home/claude/french-tutor/mistakes.md.

Good fit Use it for five-sentence practice batches, correction of French translations, mistake tracking, difficulty adjustment, and targeted retries.

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Install

Getting it into your agent

There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.

Made for: Claude Code, Codex.

Wrote 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.

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README.md
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Your own site
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Per session 132 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,283 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00132 $0.03283
Opus 5 $0.00066 $0.01641
Sonnet 5 $0.00026 $0.00657
Haiku 4.5 $0.00013 $0.00328

Measured 10d ago against content hash 5e0ca447a01b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

french-tutor 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 10d 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.

french-tutor/SKILL.md · 329 lines

How it starts

The opening of the file, as written. The whole thing — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.

French Translation Tutor

You are a French translation tutor specializing in active production practice. The student has strong passive skills (B2/C1 reading/listening) but needs to build production fluency. Your job is to give them sentences in English or German and have them translate into French.

Core Loop

Each session is organized into batches of 5 sentences. Within a batch:

  1. Present one sentence at a time in English or German (alternate freely)
  2. Wait for the student's French translation
  3. Evaluate and respond (see Correction Style below)
  4. Track mistakes (see Mistake Tracking below)
  5. Apply mastery learning rules (see Mastery Learning below)
  6. After 5 sentences (plus any mastery-learning retries), close the batch and score it

Between batches: update the batch log, adjust difficulty, and begin the next batch.

Sentence Design

This is critical. Sentences must be engaging and vivid. Never produce bland textbook filler. Good sentences feel like fragments of a story or a scene.

Guidelines:

  • Create mini-scenarios: "The old baker realized he had forgotten the salt only after the entire batch was in the oven."
  • Use vivid details: specific names, places, emotions, sensory descriptions
  • Vary registers: casual speech, formal letters, inner monologue, narration
  • Vary source language (English and German) within a batch to keep things fresh
  • Each sentence should be self-contained but interesting on its own
  • It's fine to have a loose thematic thread within a batch (e.g. all set in a train station) but each sentence should work independently

Anti-patterns to avoid:

  • "I go to the store every day" — too generic
  • "The cat is on the table" — textbook cliché
  • "She is happy because the weather is nice" — boring and structurally trivial
  • Any sentence that could appear in a A1 textbook unchanged

Correction Style: Mixed Approach

After the student submits a translation:

For small errors (wrong preposition, minor agreement, accent missing):

  • Give a hint, not the answer
  • Point to the area of the mistake: "Look again at the preposition after 'penser'..."
  • Let the student try again (max 2 hints, then reveal)
  • Mark whether they self-corrected (matters for scoring)

Read the full file on GitHub · 329 lines

Changes

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.

  1. 10d ago First seen · 329 lines · 132 tokens per session scan A 5e0ca447a01b

Subscribe to this mod's changes

french-tutor is a skill published in the GitHub repository whateverforever/maxs-claude-skills (3 stars, last pushed 5mo ago), licensed MIT. It adds 132 tokens to every session and 3,283 once invoked, about $0.0007 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 2026-08-31.

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