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 LUNARTECH-X/superpowers --skill academic-pipelinegit clone --depth 1 https://github.com/LUNARTECH-X/superpowersWrote 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/lunartech-x/superpowers/academic-pipeline)<a href="https://agentmods.dev/skills/lunartech-x/superpowers/academic-pipeline"><img src="https://agentmods.dev/badge/skills/lunartech-x/superpowers/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/lunartech-x/superpowers/academic-pipeline"><img src="https://agentmods.dev/badge/skills/lunartech-x/superpowers/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 | $0.07680 |
| Opus 5 | $0.00053 | $0.03840 |
| Sonnet 5 | $0.00021 | $0.01536 |
| Haiku 4.5 | $0.00011 | $0.00768 |
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 10d 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- academic-pipeline — 95% identical, 4 lines differ
- academic-pipeline — 94% identical, 43 lines differ
- academic-pipeline — 84% identical, 89 lines differ
How it starts
The opening of the file, as written. The whole thing — 593 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Academic Pipeline v3.7.0 — 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.
v3.6.3 (opt-in): Set ARS_PASSPORT_RESET=1 to promote FULL checkpoints to context-reset boundaries. Use resume_from_passport=<hash> in a fresh session to continue from the recorded stage. See references/passport_as_reset_boundary.md.
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)
Resume from passport (cross-session context reset, opt-in):
resume_from_passport=<hash> [stage=<n>] [mode=<m>]
--> Loads the Material Passport (Schema 9), locates the kind: boundary entry matching <hash>, and confirms it has no later kind: resume entry consuming it. If pending_decision is set, the decision prompt fires first to capture the user's branch choice for the audit ledger; the prompt is never skipped, even when the user supplies stage=. After the prompt (or immediately if no pending_decision), the next stage is determined by: (a) stage=<n> CLI override if provided, else (b) the matched option's next_stage, else (c) the next field recorded in the boundary entry. CLI stage=/mode= overrides win over option routing.
- Gate (emit):
ARS_PASSPORT_RESET=1must be set in the emitting session. Without the flag, nokind: boundaryentries are written and there is nothing to resume from. - Gate (resume): No flag required. Any session can invoke
resume_from_passport=<hash>against a passport that carries a valid boundary entry matching the hash. - Intent: Invoke in a fresh Claude Code session. Resuming within the same session that emitted the boundary provides no token savings and may drop still-live in-session context.
- Stage: Any. Resumes at whatever stage the routing rules above determine.
- Reference:
references/passport_as_reset_boundary.md— see §"resume_from_passportmode contract".
What ships with it
27 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.
- agents/collaboration_depth_agent.md 8.9 KB
- agents/integrity_verification_agent.md 24 KB
- agents/pipeline_orchestrator_agent.md 56 KB
- agents/state_tracker_agent.md 18 KB
- examples/full_pipeline_example.md 17 KB
- examples/integrity_failure_recovery.md 26 KB
- examples/mid_entry_example.md 12 KB
- references/adapters/.gitkeep 0 B
- references/adapters/overview.md 9.5 KB
- references/ai_research_failure_modes.md 15 KB
- references/changelog.md 5.8 KB
- references/claim_verification_protocol.md 2.7 KB
- references/external_review_protocol.md 6.2 KB
- references/integrity_review_protocol.md 2.3 KB
- references/literature_corpus_consumers.md 9.8 KB
- references/mode_advisor.md 7.8 KB
- references/passport_as_reset_boundary.md 17 KB
- references/pipeline_state_machine.md 15 KB
- references/plagiarism_detection_protocol.md 13 KB
- references/process_summary_protocol.md 12 KB
- references/progress_dashboard_template.md 1.5 KB
- references/reinforcement_content.md 1.3 KB
- references/reproducibility_audit.md 2.3 KB
- references/score_trajectory_protocol.md 3.7 KB
- references/team_collaboration_protocol.md 8.9 KB
- references/two_stage_review_protocol.md 1.4 KB
- templates/pipeline_status_template.md 3.7 KB
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.
- 10d ago First seen · 593 lines · 106 tokens per session scan A 925291b1d270
academic-pipeline is a skill published in the GitHub repository LUNARTECH-X/superpowers (16 stars, last pushed 3mo ago), licensed MIT. It adds 106 tokens to every session and 7,680 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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