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 ShaishavMaisuria/research-paper-lifecycle-skills --skill orchestrate-papergit clone --depth 1 https://github.com/ShaishavMaisuria/research-paper-lifecycle-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/shaishavmaisuria/research-paper-lifecycle-skills/orchestrate-paper)<a href="https://agentmods.dev/skills/shaishavmaisuria/research-paper-lifecycle-skills/orchestrate-paper"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/orchestrate-paper/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/shaishavmaisuria/research-paper-lifecycle-skills/orchestrate-paper"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/orchestrate-paper.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 | $0.00211 | $0.03051 |
| Opus 5 | $0.00105 | $0.01525 |
| Sonnet 5 | $0.00042 | $0.00610 |
| Haiku 4.5 | $0.00021 | $0.00305 |
Grade A, and why
orchestrate-paper 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 13d 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 — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestrate Paper
The conductor. The author brings a technical idea, their experiments, and a target — a venue, or "help me pick one." This skill sets the goal ("submission-ready for venue X by deadline D") and runs a goal → plan → execute → verify → reflect loop across the whole lifecycle: it plans which sub-skills run and in what order, invokes them, checkpoints with the author at every stage gate, and uses external, measurable signals — not its own say-so — to confirm each stage actually moved the paper forward before going on.
It does not write the paper for the author and it never submits anything. It
coordinates the specialists (each of which is its own skill) and keeps a
durable, reviewable record in paper-workspace/ so the author can pause,
inspect, reject, and resume at any point.
This skill follows a few non-negotiable working principles at every checkpoint: name assumptions, show competing readings, surface tradeoffs, stop when confused, verify live, and keep the author the author.
When to use
- "Take my idea + results to a submission-ready paper for VENUE." / "Run the whole pipeline." / "Be my copilot from idea to submission."
- "What's the plan from here?" / "What's done, what's next, what's blocking me?"
- Mid-cycle coordination: "I just got reviews back — what now?" or "we were accepted; drive camera-ready + artifacts."
- The author has many skills available and wants one entry point that sequences them instead of running ~20 by hand.
When NOT to use
- A single, well-scoped task ("polish this paragraph", "check my citations"). Call that one skill directly — the orchestration overhead isn't worth it.
- The author wants the text written for them with no review. That is not what this is; it is a copilot, and the author authors.
Inputs
- The idea + experiments — what the paper claims and the evidence the author already has. The orchestrator never invents results to fill gaps; a missing experiment is surfaced as a blocker, not fabricated.
- The target — a venue+track, or
help me pick(routes throughselect-venuefirst). Either way, the live CFP is re-verified, never trusted from a cached profile. - Whatever draft exists — from a blank idea to a near-final
.tex. The plan adapts to the current state (see the state script below). .paper-memory/— positioning (profile.yml), accumulatedlessons.md, anddecisions.mdfollowing thepaper-memory-convention.mdpattern. Read at start.
What ships with it
3 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.
- 13d ago First seen · 231 lines · 211 tokens per session scan A bbc2f8c0469b
orchestrate-paper is a skill published in the GitHub repository ShaishavMaisuria/research-paper-lifecycle-skills (42 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 211 tokens to every session and 3,051 once invoked, about $0.0011 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.
Other skills, from other repositories
aaai-reproducibility
Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across…
aaai-submission
Use when auditing an AAAI main technical track submission for OpenReview readiness, double-blind anonymity, page limits, reproducibility checklist, supplementary material, author limits, multiple-submission policy, and AAAI AI-use policy compliance.
aaai-topic-selection
Use when deciding whether a project is a strong AAAI submission across its broad AI scope, should be reframed or routed to a dedicated track such as AI for Social Impact or AI Alignment, or should instead go to IJCAI, NeurIPS, ICML, ICLR, AISTATS, UAI, ACL, CVPR, KDD, CHI, ICRA, or another specialist venue.
acl-author-response
Use when drafting an ACL author response inside an ACL Rolling Review cycle on OpenReview, covering the response window before meta-review, reviewer discussion dynamics, score-change strategy, flagging review issues to the area chair, anonymity rules, and deciding between responding now versus revising for a later ARR…
acl-camera-ready
Use when preparing an accepted ACL main-conference or Findings paper for camera-ready, covering the extra content page, de-anonymization and acknowledgements, AI-assistance disclosure, keeping the Limitations section, ACL Anthology metadata and CC BY 4.0 publication, meta-review-driven edits, and presentation-mode…
acl-experiments
Use when designing or auditing experiments for an ACL paper, covering tuned LLM baselines, multi-dataset and multilingual evaluation, statistical significance and variance, human evaluation with agreement reporting, contamination and prompt-sensitivity controls, ablations, and error-analysis expectations in NLP…