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 academic-writinggit 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/academic-writing)<a href="https://agentmods.dev/skills/khaledsaeed18/dotclaude/academic-writing"><img src="https://agentmods.dev/badge/skills/khaledsaeed18/dotclaude/academic-writing/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/academic-writing"><img src="https://agentmods.dev/badge/skills/khaledsaeed18/dotclaude/academic-writing.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 | $0.00113 | $0.01271 |
| Opus 5.5 | $0.00045 | $0.00508 |
| Sonnet 5.5 | $0.00023 | $0.00254 |
| Haiku 4.5 | $0.00011 | $0.00127 |
Grade A, and why
academic-writing 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Academic prose has one job: let a sceptical reader check a claim. Every device below exists for that reader. Write for the examiner who will read chapter 4 at 11pm looking for a reason to ask a hard question at the defence.
Before writing a section
- Read the research question record and the outline for the chapter. If neither exists, ask for the section's purpose in one sentence; do not start from a blank page.
- Read the notes or results the section must draw on (
research/notes/, result tables, figures). Everything you state must be traceable to one of them or to the student. - Confirm the target: length, the department's style guide, the citation style, and whether the document is LaTeX or Word (this changes how you write cross-references and citations, never what you write).
Section by section
Abstract (150 to 300 words, written last): context in one sentence; the problem or gap; what was done (method, scale); the main result with a number; what it means. No citations, no abbreviations undefined, no "this thesis is organised as follows".
Introduction: the problem and why it matters now; the gap in one paragraph with two or three citations; the research questions verbatim; the contributions as a short list, each a noun phrase a reader could check; the thesis structure in three sentences. Length: 5 to 8% of the thesis.
Related work / background: comes from lit-review-synthesis; every paragraph opens with a claim about the field and ends by relating it to this thesis. The last paragraph is the gap.
Method: what was done, precisely enough to replicate. Past tense, passive voice acceptable ("the data were collected"), but name the agent when it matters ("the author labelled the samples"). Subsections follow the sub-questions. Design decisions get one sentence of justification each, with the alternative rejected. Threats to validity live here or in a dedicated section, never omitted.
Results: what was observed, without interpretation. Each table and figure is introduced by a sentence that says what to look at ("Table 4 shows that variant B halves latency at all input sizes"), followed by the exact numbers, then the caveat. Report variance (standard deviation, confidence interval, number of runs). Present tense for what the data show.
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 · 58 lines · 113 tokens per session scan A 7509178434a7
academic-writing is a skill published in the GitHub repository KhaledSaeed18/dotclaude (5 stars, last pushed 2d ago), licensed MIT. It adds 113 tokens to every session and 1,271 once invoked, about $0.0005 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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