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/first-fluke/fullstack-starter/oma-academic-writingnpx skills add first-fluke/fullstack-starter --skill oma-academic-writinggit clone --depth 1 https://github.com/first-fluke/fullstack-starterWrote 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/first-fluke/fullstack-starter/oma-academic-writing)<a href="https://agentmods.dev/skills/first-fluke/fullstack-starter/oma-academic-writing"><img src="https://agentmods.dev/badge/skills/first-fluke/fullstack-starter/oma-academic-writing.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 5.1 | $0.00114 | $0.03108 |
| Opus 5 | $0.00057 | $0.01554 |
| Sonnet 5 | $0.00023 | $0.00622 |
| Haiku 4.5 | $0.00011 | $0.00311 |
Grade A, and why
oma-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 2d 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.
This is a copy
100% identical to oma-academic-writing — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Academic Writing: Publication-Grade English Prose
Scheduling
Goal
Produce, revise, and audit publication-grade academic English prose so that every output simultaneously satisfies the Sentence Structure Protocol, Verb Protocol, Hedging Protocol, and Anti-AI Compliance Checklist, with every claim mapped to verifiable evidence.
Intent signature
- "draft this essay / report / executive summary / conclusion / literature review"
- "rewrite this paragraph in academic English"
- "polish this draft to top-band quality" / "revise to match the rubric"
- "run an anti-AI audit on this prose"
- "check sentence structure variety" / "fix monotonous rhythm"
- "the prose sounds AI-generated, make it pass"
- "verify claims against evidence" / "reverse outline this section"
When to use
- Drafting or revising academic reports, essays, or analysis sections
- Writing executive summaries, conclusions, or literature reviews
- Rewriting AI-sounding prose into natural academic English
- Polishing draft text to achieve top-band rubric quality (HD, A, top-band, etc.)
- Reviewing prose for sentence variety, verb quality, hedging, and anti-AI compliance
- Any task requiring formal academic English output bound by a rubric
When NOT to use
- Translation tasks → use
oma-translation - Source discovery, citation gathering, or scholarly literature search → use
oma-scholar - Rubric / assignment-spec parsing and task decomposition → use
oma-pm - Code documentation, README, or API reference text → use the relevant domain skill (
oma-frontend,oma-backend,oma-mobile,oma-db, etc.) - Informal communication, chat, or marketing copy → no skill needed
- Non-English academic writing → call
oma-translationfor the target language after drafting in English
Expected inputs
mode: one ofdraft|revise|reviewrubric_or_constraint: assignment brief, rubric file, or word/structure limits (path or inline text)existing_draft: prior text to revise or audit (path or inline text); required forreviseandreviewsource_data: available evidence, figures, citations the writer may usetarget_register: defaults to formal academic English with American spelling (en-US)
What ships with it
4 files 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.
- 2d ago First seen · 183 lines · 114 tokens per session scan A f763b39ac8b6
oma-academic-writing is a skill published in the GitHub repository first-fluke/fullstack-starter (222 stars, last pushed 2d ago), licensed MIT. It adds 114 tokens to every session and 3,108 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to oma-academic-writing, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
retro-learn
Convert delivery findings into skill, eval, workflow, and documentation improvements.
system-design-case-catalog
Answer classic system design problems as constraint-to-solution sketches and coach interview practice: URL shortener, rate limiter, news feed, chat, notification, autocomplete, crawler, unique id. Use for interview practice or naming the closest known shape for a new problem.
frontend-feature
Build a new page, view, or data-driven feature in the Next.js frontend. Use when adding a route under the dashboard/marketing area, wiring UI to a backend endpoint, adding client state, or creating a localized page. Covers App Router, data fetching, Zustand stores, and i18n.
dev-fix
Unified developer workflow for fixing bugs. Analyzes issue-tracker context, cross-checks docs/code, proposes a solution, implements the fix, verifies locally, and delivers a PR/MR.
sdlc
Route a task to the next synced SDLC workflow based on current artifacts and repo state.
Skill Creator
Standards for creating new High-Density Agent Skills with optimal token economy.