Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add waterwoods-ai/auto-academic/plugin install auto-academicWrote 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/waterwoods-ai/auto-academic/academic-pipeline)<a href="https://agentmods.dev/skills/waterwoods-ai/auto-academic/academic-pipeline"><img src="https://agentmods.dev/badge/skills/waterwoods-ai/auto-academic/academic-pipeline/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/waterwoods-ai/auto-academic/academic-pipeline"><img src="https://agentmods.dev/badge/skills/waterwoods-ai/auto-academic/academic-pipeline.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 | $0.00106 | $0.09845 |
| Opus 5 | $0.00053 | $0.04922 |
| Sonnet 5 | $0.00021 | $0.01969 |
| Haiku 4.5 | $0.00011 | $0.00984 |
Grade A, and why
academic-pipeline 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 — 832 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Academic Pipeline v2.7 — Full Academic Research Workflow Orchestrator
A lightweight orchestrator that manages the complete academic pipeline from research exploration to final manuscript. It does not perform substantive work — it only detects stages, recommends modes, dispatches skills, manages transitions, and tracks state.
v2.0 Core Improvements:
- Mandatory user confirmation checkpoints — Each stage completion requires user confirmation before proceeding to the next step
- Academic integrity verification — After paper completion and before review submission, 100% reference and data verification must pass
- Two-stage review — First full review + post-revision focused verification review
- Final integrity check — After revision completion, re-verify all citations and data are 100% correct
- Reproducible — Standardized workflow producing consistent quality assurance each time
- Process documentation — After pipeline completion, automatically generates a "Paper Creation Process Record" PDF documenting the human-AI collaboration history
Quick Start
Full workflow (from scratch):
I want to write a research paper on the impact of AI on higher education quality assurance
--> academic-pipeline launches, starting from Stage 1 (RESEARCH)
Mid-entry (existing paper):
I already have a paper, help me review it
--> academic-pipeline detects mid-entry, starting from Stage 2.5 (INTEGRITY)
Revision mode (received reviewer feedback):
I received reviewer comments, help me revise
--> academic-pipeline detects, starting from Stage 4 (REVISE)
Execution flow:
- Detect the user's current stage and available materials
- Recommend the optimal mode for each stage
- Dispatch the corresponding skill for each stage
- After each stage completion, proactively prompt and wait for user confirmation
- Track progress throughout; Pipeline Status Dashboard available at any time
Trigger Conditions
Trigger Keywords
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 · 832 lines · 106 tokens per session scan A b4e5620540b9
academic-pipeline is a skill published in the GitHub repository waterwoods-ai/auto-academic (6 stars, last pushed 5mo ago), licensed MIT. It adds 106 tokens to every session and 9,845 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 2026-08-31.
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