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 reflect-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/reflect-paper)<a href="https://agentmods.dev/skills/shaishavmaisuria/research-paper-lifecycle-skills/reflect-paper"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/reflect-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/reflect-paper"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/reflect-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 | $0.00127 | $0.01566 |
| Opus 5 | $0.00063 | $0.00783 |
| Sonnet 5 | $0.00025 | $0.00313 |
| Haiku 4.5 | $0.00013 | $0.00157 |
Grade A, and why
reflect-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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reflect Paper
Run a structured reflection loop over a research-paper draft. Treat this as two separate perspectives, then merge them into one revision plan:
- Researcher pass — technical truth, evidence, citations, venue fit, novelty, limitations, reviewer risk.
- Writer pass — narrative, framing, section structure, abstract, related work placement, prose, figures/tables, reader flow.
This is an orchestration skill: it calls on sibling skills when their narrower checks are needed, but it owns the reflection protocol and final synthesis.
If the runtime supports delegated agents or subagents, split the reflection into two independent workers:
- Send a Researcher worker the draft, target venue/context, and the Researcher pass checklist only.
- Send a Writer worker the draft, target venue/context, and the Writer pass checklist only.
- Merge both outputs yourself; do not let either worker decide the final verdict alone.
If delegation is unavailable, run the same passes sequentially. Keep separate notes for each pass so technical-risk findings do not flatten writing feedback, and writing polish does not hide correctness concerns.
When to use
- "Reflect on this paper before I submit"
- "Run a research agent and writer agent on my draft"
- "Critique this draft from both technical and writing angles"
- "Give me a revision plan"
- "What should I fix before sending this to my advisor / reviewers?"
- "Do a final paper reflection pass"
Inputs
- The draft: LaTeX source, PDF, markdown, Word-exported text, or pasted sections.
- Optional: target venue or CFP URL.
- Optional: bibliography file, related-work notes, reviews, or advisor feedback.
- Optional: the user's current goal, such as submission readiness, camera-ready polish, rebuttal, or presentation prep.
Process
1. Scope The Reflection
Identify the lifecycle stage and what "good" means for this pass:
| Stage | Primary concern |
|---|---|
| Early draft | Missing contribution, weak framing, incomplete evidence. |
| Pre-submission | Venue fit, page budget, anonymization, citation reliability, reviewer risk. |
| Rebuttal | Review coverage, evidence anchors, tone, response budget. |
| Camera-ready | Required final-file steps, de-anonymization, acknowledgments, source consistency. |
| Presentation | Talk story, timing, Q&A risk, slide/poster readability. |
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 · 173 lines · 127 tokens per session scan A fdecf1643627
reflect-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 127 tokens to every session and 1,566 once invoked, about $0.0006 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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