Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add OleksiiDotsenko/english-exam-coach/plugin install english-exam-coachWrote 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/oleksiidotsenko/english-exam-coach/writing-evaluator)<a href="https://agentmods.dev/skills/oleksiidotsenko/english-exam-coach/writing-evaluator"><img src="https://agentmods.dev/badge/skills/oleksiidotsenko/english-exam-coach/writing-evaluator/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/oleksiidotsenko/english-exam-coach/writing-evaluator"><img src="https://agentmods.dev/badge/skills/oleksiidotsenko/english-exam-coach/writing-evaluator.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 | $0.00117 | $0.01970 |
| Opus 5 | $0.00059 | $0.00985 |
| Sonnet 5 | $0.00023 | $0.00394 |
| Haiku 4.5 | $0.00012 | $0.00197 |
Grade A, and why
writing-evaluator 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 12d 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing Evaluator
Generates original writing prompts and evaluates responses. Paths are
relative to ${CLAUDE_PLUGIN_ROOT} (if unset, resolve relative to the plugin
root — the directory two levels up from this file, i.e. the folder containing
data/ and skills/).
When to use
The user pasted a piece of writing for assessment, OR asked for a practice writing task in a named exam format, OR asked how to improve exam writing.
Steps
-
Identify exam + level + task type. If unclear, ask once. When EVALUATING pasted writing, also obtain the exact task prompt as it was set — the IELTS question, the two given points for a B2 essay, the TOEFL email's three content points, the letter's bullets — plus whether it was written timed and in how long. Task fulfilment (were the required points covered, right genre, word count) is the first-ranked criterion and caps the band; without the prompt, say so and mark Task Achievement provisionally rather than guessing. Load:
data/exam-formats/<exam-id>.md(format, word count, timing, criteria names)data/cefr/writing-descriptors.md(assessment anchors)data/cefr/calibration-anchors.md(leveled reference samples)skills/writing-evaluator/references/task-anatomy.md(structure and register expectations per task type)
-
If GENERATING a prompt: produce an ORIGINAL prompt matching the format's structure, word count and timing (seed examples:
data/item-bank/seed/writing-prompts.md— imitate shape, never reuse content). Pitch the prompt's cognitive/topic demand to the level, not just its length: B1 concrete/personal; B2 a familiar issue to take a stance on; C1 abstract, requiring evaluation/weighing; C2 nuanced or counter-intuitive. (calibration-anchors.mdshows what an at-level answer looks like — aim the prompt so a level-appropriate answer lands there.) State the time limit and word target. Offer to time the attempt: note the start time, and compute elapsed seconds when the answer arrives.
What ships with it
1 file 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.
- 12d ago First seen · 140 lines · 117 tokens per session scan A abe1b232f510
writing-evaluator is a skill published in the GitHub repository OleksiiDotsenko/english-exam-coach (8 stars, last pushed 1mo ago), licensed MIT. It adds 117 tokens to every session and 1,970 once invoked, about $0.0006 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.
Other skills, from other repositories
oral-english-practice
A Claude Code skill that stores and analyses spoken-English practice completed in the Claude app. The app handles the conversation; this skill keeps reports, scores, mistakes, progress trends, and the next practice focus.
language-coach
Language coaching for every prompt. Use when the user runs /language-coach with any sub-command (setup, native, target, style, response, goal, mode, focus, band, level, status, off, on). Routes to the correct action based on the argument provided.
language-review
Analyze language learning progress from local data. Use when the user runs /language-coach:language-review or asks to review their progress, see their band history, check improvement trends, or analyze their IELTS score data.
learning-and-development
Builds capability — skills gaps, career frameworks, training that transfers to the job, and internal mobility. Use this to design a career ladder, close a capability gap, decide whether to build or hire a skill, structure onboarding into a role, or work out why training keeps failing to change anything.
diagnose
A short question-based assessment of a pilot's current skill level. It produces a profile and saves it in the connected browser or database.
lesson-close
A workflow for finishing the day's lesson file, recording its status and duration, then saving it to the personal-guide GitHub repository.