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 echoleesong/claude-skills-plugin --skill academic-pipelinegit clone --depth 1 https://github.com/echoleesong/claude-skills-pluginWrote 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/echoleesong/claude-skills-plugin/academic-pipeline)<a href="https://agentmods.dev/skills/echoleesong/claude-skills-plugin/academic-pipeline"><img src="https://agentmods.dev/badge/skills/echoleesong/claude-skills-plugin/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/echoleesong/claude-skills-plugin/academic-pipeline"><img src="https://agentmods.dev/badge/skills/echoleesong/claude-skills-plugin/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 | $0.08775 |
| Opus 5 | $0.00053 | $0.04387 |
| Sonnet 5 | $0.00021 | $0.01755 |
| Haiku 4.5 | $0.00011 | $0.00877 |
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 11d 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
94% identical to academic-pipeline — 43 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 — 624 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Academic Pipeline v3.11.1 — 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.
Routing discipline (v3.9.2): see
.claude/CLAUDE.md"Routing Discipline (v3.9.2)" +shared/references/intent_clarification_protocol.mdfor cross-skill routing rules. This skill assumes routing has already settled — ambiguous cross-phase materials should have been clarified upstream.
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.
v3.8 (opt-in): Set ARS_CLAIM_AUDIT=1 to enable the L3 claim-faithfulness audit gate at the Stage 4 → Stage 5 transition. When the flag is set, the orchestrator dispatches claim_ref_alignment_audit_agent after the v3.7.1 Cite-Time Provenance Finalizer and before formatter_agent's hard gate. The audit emits claim_audit_results[] + uncited_assertions[] + claim_drifts[] + constraint_violations[] + audit_sampling_summaries[] aggregates per the 8-row matrix; HIGH-WARN classes gate-refuse output via the formatter REFUSE rules 6-10. Default OFF for v3.8.0 — ramp-on plan deferred to post-calibration evidence (spec §5 mode flag rationale). See agents/claim_ref_alignment_audit_agent.md and the orchestrator §3.6 prose.
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
What ships with it
29 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/claim_ref_alignment_audit_agent.md 31 KB
- agents/collaboration_depth_agent.md 8.9 KB
- agents/integrity_verification_agent.md 24 KB
- agents/pipeline_orchestrator_agent.md 67 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 9.6 KB
- references/ai_research_failure_modes.md 15 KB
- references/changelog.md 5.8 KB
- references/claim_audit_calibration_protocol.md 13 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.
- 11d ago First seen · 624 lines · 106 tokens per session scan A 705c46924593
academic-pipeline is a skill published in the GitHub repository echoleesong/claude-skills-plugin (4 stars, last pushed 3mo ago), licensed MIT. It adds 106 tokens to every session and 8,775 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to academic-pipeline, differing in 43 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…