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 assess-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/assess-paper)<a href="https://agentmods.dev/skills/shaishavmaisuria/research-paper-lifecycle-skills/assess-paper"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/assess-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/assess-paper"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/assess-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 | $0.00199 | $0.01941 |
| Opus 5 | $0.00100 | $0.00971 |
| Sonnet 5 | $0.00040 | $0.00388 |
| Haiku 4.5 | $0.00020 | $0.00194 |
Grade A, and why
assess-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 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Assess Paper
The single command that tells an author where they stand and explains why, so a non-expert isn't left staring at five separate tool outputs. It does not re-implement any check; it runs the specialist skills and turns their results into one readable Paper Health Report that leads with strengths, then risks, then a ranked to-do list.
Pairs with orchestrate-paper (which drives the full lifecycle) — assess-paper is the read-only "where am I right now" snapshot you can run at any point. Copilot, not pilot: it reports and explains, it never edits the paper or submits anything.
When to use
- The author wants one overview instead of running five skills and stitching the results together.
- Early ("how far off am I?") or late ("am I ready to submit?").
- A co-author or advisor wants a quick, honest state-of-the-paper.
When NOT to use it (say this plainly)
- You want one specific check — run that skill directly (e.g. just citations →
verify-citations). - You want fixes applied — this skill only diagnoses; hand each fix to the skill that owns it.
- You want an acceptance probability or award forecast — no tool can give one honestly; this skill refuses to.
Inputs
- The draft: a
.texsource tree, a compiled PDF, or a readable draft. Processed transiently — never copied into this repo. - The target venue and track (what counts as "ready" differs by venue). Ask if unstated; run against the nearest family default and say so if no profile exists.
- Optional:
.paper-memory/profile.yml(positioning) andlessons.md(recurring weaknesses), if present.
What it consolidates
| Dimension | Skill it runs | What it contributes to the report |
|---|---|---|
| Will it get desk-rejected? | preflight-check |
compliance blockers (page limit, anonymization, missing sections) |
| Are the citations real? | verify-citations |
fabricated / retracted / duplicate references |
| Is it original? | check-originality |
plagiarism / self-recycling overlap |
| Does it match strong work at the venue? | benchmark-paper |
venue-fit scorecard + weakest dimensions |
| What will reviewers say? | simulate-reviewers |
strengths, weaknesses, rubric scores, decision-risk |
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 · 110 lines · 199 tokens per session scan A c05b65833d7c
assess-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 199 tokens to every session and 1,941 once invoked, about $0.0010 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
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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…