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 polish-prosegit 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/polish-prose)<a href="https://agentmods.dev/skills/shaishavmaisuria/research-paper-lifecycle-skills/polish-prose"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/polish-prose/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/polish-prose"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/polish-prose.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 | $0.02649 |
| Opus 5 | $0.00105 | $0.01324 |
| Sonnet 5 | $0.00042 | $0.00530 |
| Haiku 4.5 | $0.00021 | $0.00265 |
Grade A, and why
polish-prose 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 — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Polish Prose
Turn an AI-flavored or overwrought draft into prose that reads like a careful researcher wrote it — without moving a single number, claim, or citation. Reviewers now pattern-match the LLM register (delve/leverage vocabulary, Moreover-stacked paragraphs, em-dash chains, uniform hedging), and a leftover "Certainly! Here is..." or "[insert citation]" is a desk-reject-grade embarrassment. This skill finds all of it deterministically, then guides a disciplined human-in-the-loop rewrite: expression changes, content does not.
When to use
- "My paper sounds like ChatGPT wrote it" / "humanize this" / "de-AI-ify"
- "Remove the AI words" / "it keeps saying delve and leverage"
- "Tighten / polish my writing" / "this is too wordy"
- "Fix my hedging" — overclaimed contributions or drowned-in-maybes results
- "Make my contribution statements active" ("a method is proposed..." → "We propose...")
- "Is my terminology consistent?" (dataset vs data set, acronym discipline, British vs American spelling)
- Called before
preflight-checkas part of the final submission pass, or after heavy drafting with any LLM assistant.
Inputs
- The draft: a
.texfile (preamble/math/verbatim are masked automatically), a.md/.txtfile, or pasted text via stdin. - Optional: the venue profile
venues/conferences/<venue>-<year>.yml(schema invenues/schema.yml) — supplies the venue family for register norms andreview.llm_policyfor AI-use disclosure duties. - Optional: a project glossary (
canonical term = variant | variantper line) if the team has already standardized terminology.
Process
-
Freeze the technical content first. Build the no-touch inventory before editing anything: every number and unit, every
\citekey, every stated result, dataset name, and system name. Snapshot it:grep -oE '[0-9][0-9.,]*\s*(%|\\%|ms|s|GB|MB|x|×)?' draft.tex | sort | uniq -c > /tmp/numbers-before.txtThe same command must produce identical output after the edit pass (step 9). If polishing would require changing a claim, stop and tell the user — that is a content decision, not a style edit.
What ships with it
6 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.
- 12d ago First seen · 206 lines · 211 tokens per session scan A ca156a4f3f27
polish-prose 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 2,649 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.
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