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 KhaledSaeed18/dotclaude --skill proofread-academicgit clone --depth 1 https://github.com/KhaledSaeed18/dotclaudeWrote 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/khaledsaeed18/dotclaude/proofread-academic)<a href="https://agentmods.dev/skills/khaledsaeed18/dotclaude/proofread-academic"><img src="https://agentmods.dev/badge/skills/khaledsaeed18/dotclaude/proofread-academic/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/khaledsaeed18/dotclaude/proofread-academic"><img src="https://agentmods.dev/badge/skills/khaledsaeed18/dotclaude/proofread-academic.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 | $0.00105 | $0.01239 |
| Opus 5.5 | $0.00042 | $0.00496 |
| Sonnet 5.5 | $0.00021 | $0.00248 |
| Haiku 4.5 | $0.00011 | $0.00124 |
Grade A, and why
proofread-academic 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 25d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Read as the examiner reads, with a pen. This skill produces findings, not a rewrite: the student stays the author, and every change is theirs to make. Report locations as file:line (or section and paragraph for Word exports).
Pass 1: structure
- Does the introduction state the research questions verbatim, and does the conclusion answer each in order?
- Does every chapter open with what it covers and close with what it established?
- Read only the first sentence of every paragraph: is it the claim? Does the sequence make an argument?
- Are headings parallel in form and specific (not "Results" for three chapters in a row)?
- Is anything promised ("Section 4.3 discusses") that does not exist?
Pass 2: consistency
- Terms: one name per concept. Build the list as you read; flag every synonym pair ("model" and "system" for the same thing) with both locations.
- Acronyms: defined at first use, then used consistently; not defined twice; not defined in the abstract and never used again. List every acronym with its first definition.
- Notation: each symbol means one thing thesis-wide; vectors, sets, and scalars typeset consistently; units consistent (ms throughout, not ms then s).
- Names: the proposed system, datasets, and baselines named identically everywhere, including figures and tables.
- Tense and voice per section (past for method and prior work, present for results and truths), and one first-person convention throughout.
Pass 3: figures, tables, equations
- Every figure and table referenced in the text before it appears, by number, with the reference resolving (
??or "Figure" with no number is a broken ref). - Captions self-contained: content, conditions, what to notice, what error bars mean and n.
- Axes labelled with units; legends readable; the same series the same colour across figures.
- Tables: units in headers, consistent decimals per column, best result marked if the text says "best".
- Equations numbered if referenced; every symbol introduced in prose near the equation.
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.
- 25d ago First seen · 83 lines · 105 tokens per session scan A f813bf547a3c
proofread-academic is a skill published in the GitHub repository KhaledSaeed18/dotclaude (5 stars, last pushed 2d ago), licensed MIT. It adds 105 tokens to every session and 1,239 once invoked, about $0.0004 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 2026-09-22.
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