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 muhammad1438/academic-writer-skills --skill ai-academic-ethicsgit clone --depth 1 https://github.com/muhammad1438/academic-writer-skillsWrote 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/muhammad1438/academic-writer-skills/ai-academic-ethics)<a href="https://agentmods.dev/skills/muhammad1438/academic-writer-skills/ai-academic-ethics"><img src="https://agentmods.dev/badge/skills/muhammad1438/academic-writer-skills/ai-academic-ethics/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/muhammad1438/academic-writer-skills/ai-academic-ethics"><img src="https://agentmods.dev/badge/skills/muhammad1438/academic-writer-skills/ai-academic-ethics.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 | $0.00000 | $0.02591 |
| Opus 5 | $0.00000 | $0.01295 |
| Sonnet 5 | $0.00000 | $0.00518 |
| Haiku 4.5 | $0.00000 | $0.00259 |
Grade A, and why
ai-academic-ethics 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 — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Academic Ethics
The integration of Large Language Models (LLMs) into academic writing has necessitated immediate and profound policy evolution across publishers, institutions, and style guide committees. The landscape is evolving rapidly — always verify current policies with your specific institution and target journal.
The Fundamental Rule Across All Publishers
AI tools cannot be listed as authors or co-authors on any research paper.
Authorship implies:
- Legal accountability for the work's integrity
- Ethical responsibility for the data and claims
- Ability to assert the integrity of research
- Capacity to hold copyright
AI systems inherently lack all of these. Assigning authorship to an AI is a violation of academic publishing standards regardless of the publisher or discipline.
What AI Can and Cannot Ethically Do
Generally Acceptable (with disclosure)
- Improving language clarity, grammar, and style
- Translating content from one language to another
- Summarising literature (with human verification of accuracy)
- Generating initial outlines or brainstorming structures
- Checking for logical consistency in arguments
- Formatting references (always verify manually)
- Generating alternative phrasings for a passage you've already written
Ethically Contested / Requires Explicit Disclosure
- Drafting substantial sections of text (even when heavily revised by the human author)
- Synthesising literature across many sources
- Generating research ideas, hypotheses, or study designs
- Processing or interpreting data
Generally Not Acceptable
- Having AI write the paper with minimal human intellectual contribution
- Presenting AI-generated arguments as your own original analysis
- Using AI to generate data or fabricate citations (a growing academic fraud risk)
- Submitting AI-generated text without any disclosure
Key principle: The human author retains full, unmitigated accountability for all AI-generated content included in a submission — for its accuracy, integrity, and originality.
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 · 235 lines · 0 tokens per session scan A bc26393366d9
ai-academic-ethics is a skill published in the GitHub repository muhammad1438/academic-writer-skills (6 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,591 tokens. 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
thesis-control
Use when AI-assisted thesis or manuscript edits risk claim drift, scope creep, loss of intended use, experiment-role promotion, or repeated revisions that fail to converge; provides author-intent control, lightweight or strict contracts, drift audits, revision escalation, and human gates.
argument-governance
Build and audit the manuscript or research-project argument system across intended use, gaps, claims, data, results, experiment roles, contributions, innovation evidence, limitations, and contribution focus. Use when a paper, thesis chapter, review article, or research project needs an explicit argument map…
manuscript-reframe
Reframe report-like academic drafts into paper-form scientific arguments while preserving or explicitly renegotiating author intent; requires an approved old-versus-proposed spine, evidence and argument baselines, analysis-role control, and post-edit drift review.
audit
Check thesis chapters for consistency before submission — contradictory numbers, terminology drift, and broken cross-references.
self-review
Review the user's own manuscript, paper, thesis chapter, rebuttal, or release packet with clean-room anti-contamination controls and, when needed, an unfamiliar-reader comprehension gate. Use for internal review, readiness checks, reviewer simulation, or claim-evidence self-audit where prior chat memory and unstated…
evidence-review
Build evidence-controlled literature reviews and gap maps with source-status labels, claim registers, citation-role plans, traceability tables, and overclaim audits. Use when drafting or auditing review papers, thesis literature reviews, scoping reviews, or evidence syntheses where adjacent-domain evidence, candidate…