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 mronkko/claude-academic-research --skill manuscript-revisiongit clone --depth 1 https://github.com/mronkko/claude-academic-researchWrote 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/mronkko/claude-academic-research/manuscript-revision)<a href="https://agentmods.dev/skills/mronkko/claude-academic-research/manuscript-revision"><img src="https://agentmods.dev/badge/skills/mronkko/claude-academic-research/manuscript-revision/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/mronkko/claude-academic-research/manuscript-revision"><img src="https://agentmods.dev/badge/skills/mronkko/claude-academic-research/manuscript-revision.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00102 | $0.01235 |
| Opus 5 | $0.00051 | $0.00617 |
| Sonnet 5 | $0.00020 | $0.00247 |
| Haiku 4.5 | $0.00010 | $0.00123 |
Grade A, and why
manuscript-revision 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.
How it starts
The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Manuscript revision
No pre-flight, no bootstrap by design. This skill is doctrine — why revision works the way it does. Execution lives in the
critic-loopskill, which runs its owncheck_configured.pypre-flight. If the user invokes the critic loop in an unconfigured project, the loop will route them to setup. Don't replicate that check here.
Core rule
Academic prose is revised against multiple parallel critic perspectives,
not polished in a single pass. After drafting (or after any substantial
revision), run the critic loop via the critic-loop skill: tests must pass
→ render → parallel critic subagents → adjudicate → revise → repeat
until no critic asks for a MAJOR revision. The loop has explicit
termination rules; do not exit early and do not paper over unresolved
MAJOR issues.
This skill is the doctrine — why revision works this way and what
the critics are for. The critic-loop skill is the procedure — how
to actually run it, with CLI flags, Agent prompts, and file schemas.
Read critic-loop for the executable details; everything below is the
justification for that procedure's shape.
Before the loop: academic-style governs prose conventions
(topic sentences, active voice, hedging, term definitions) at drafting
time. Applying it before the first critic-loop run reduces how many
MAJOR/MINOR style issues the argument critic raises — fewer iterations
to convergence. This skill and critic-loop cover when and why to
revise; academic-style covers how the prose should read throughout.
Why a loop, not a pass
A single critic produces a shallow pass. Four differently-framed critics catch non-overlapping classes of problem — each perspective covers one independent axis on which an academic paper can fail:
- evidence — are the paper's factual claims honestly supported by the sources and data it invokes? Catches fabricated findings, direction reversals, misattributed citations, and prose numbers that don't match the pipeline output.
- method — is the procedure defensible and transparently disclosed? Catches causal overreach, thin limitations, missing validity threats, and under-disclosed tools / prompts / models. Reviewer #2 energy.
- argument — does the prose make a coherent case from research question to contribution? Catches scope drift, structural incoherence, one-paper-at-a-time narration in review papers, undefined terms, and framing that doesn't match the target venue.
- expert — does the manuscript hold up against what a senior reviewer in the field already knows? Catches missing seminal works, dated framings, contradictions with well-established findings, and claimed "gaps" that aren't actually gaps.
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 · 100 lines · 102 tokens per session scan A 3733d359945c
manuscript-revision is a skill published in the GitHub repository mronkko/claude-academic-research (23 stars, last pushed 7d ago), licensed MIT. It adds 102 tokens to every session and 1,235 once invoked, about $0.0005 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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