Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/JeanDiable/academic-research-pluginnpx agentmods add skills/jeandiable/academic-research-plugin/homework-machineWrote 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/jeandiable/academic-research-plugin/homework-machine)<a href="https://agentmods.dev/skills/jeandiable/academic-research-plugin/homework-machine"><img src="https://agentmods.dev/badge/skills/jeandiable/academic-research-plugin/homework-machine/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/jeandiable/academic-research-plugin/homework-machine"><img src="https://agentmods.dev/badge/skills/jeandiable/academic-research-plugin/homework-machine.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 | $0.00102 | $0.03659 |
| Opus 5 | $0.00051 | $0.01829 |
| Sonnet 5 | $0.00020 | $0.00732 |
| Haiku 4.5 | $0.00010 | $0.00366 |
Grade A, and why
homework-machine 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 8d 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 — 382 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
The homework-machine skill provides an end-to-end pipeline for completing university assignments and coursework. It automates the entire workflow from requirement analysis through final deliverable assembly, including:
- Requirement Analysis — Parse assignment specifications and extract all deliverables
- Research Phase — Conduct literature search for background and methods
- Code Implementation — Write production-quality code with comprehensive tests
- Report Writing — Generate academic reports with proper citations and formatting
- Paraphrasing — Automatic anti-plagiarism via translation round-trip (macOS only)
- Deliverable Assembly — Collect all outputs with submission checklist
The workflow produces publication-ready reports, tested code, and all supporting materials needed for submission.
Arguments
<assignment>(required) — Path to assignment PDF or plain text file containing assignment requirements--format(optional, default:latex) — Output report format:latexordocx--language(optional, default:English) — Report writing language for the academic report
Example usage:
homework-machine /path/to/assignment.pdf --format latex --language English
homework-machine "assignment_text.txt" --format docx
Setup
Before running this skill, ensure all dependencies are installed:
pip install -r "BASE_DIR/scripts/requirements.txt"
If using .docx output format, also install the Word document library:
pip install python-docx
Verify that the following helper scripts exist in BASE_DIR/scripts/:
paper_search.py— Academic paper search and retrievalbibtex_utils.py— BibTeX citation managementtranslate_roundtrip.py— Translation-based paraphrasing (macOS only)
Workflow
The homework-machine executes 6 phases in sequence. After Phase 1, the user must explicitly confirm the plan before proceeding.
Phase 1 — Analyze Assignment
- Read the Assignment
- If the input is a PDF, read it using appropriate tools
- Paginate large PDFs (>20 pages) to avoid context overflow
- If the input is a text file, read the entire content
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.
- 8d ago First seen · 382 lines · 102 tokens per session scan A d5d3cabfe770
homework-machine is a skill published in the GitHub repository JeanDiable/academic-research-plugin (20 stars, last pushed 5mo ago), licensed MIT. It adds 102 tokens to every session and 3,659 once invoked, about $0.0005 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 2026-08-30.
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