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 mathbullet/skills --skill paper-detailsgit clone --depth 1 https://github.com/mathbullet/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/mathbullet/skills/paper-details)<a href="https://agentmods.dev/skills/mathbullet/skills/paper-details"><img src="https://agentmods.dev/badge/skills/mathbullet/skills/paper-details.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 21 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00097 | $0.03074 |
| Opus 5 | $0.00048 | $0.01537 |
| Sonnet 5 | $0.00019 | $0.00615 |
| Haiku 4.5 | $0.00010 | $0.00307 |
Grade A, and why
paper-details 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 8d 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 — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper Details
Conventions for producing a detailed Markdown explainer of an academic paper. The aim of this skill is to describe the paper accurately, not to critique it.
This skill follows the shared sourced-writing conventions defined in documenting-with-sources. Read documenting-with-sources before drafting.
1. Deliverable structure
1.0 Output location
Write the explainer as a .md file under the project's reports/ directory, where "the project" is the root that contains the source paper PDF. Create the directory if it does not exist.
- Path:
{project-root}/reports/{paper-filename-base}.md - Example: if the PDF is at
/path/to/project/papers/foo.pdf, the output is/path/to/project/reports/foo.md
Do not write next to the PDF, and do not write at the project root. Do not ask the user for the output path — determine it mechanically by the rule above.
1.1 Opening
In this order:
- Title (
# {paper title} — Detailed Explainer) - Bibliographic info (authors, affiliations, venue, year, arXiv/DOI, URL)
- Full abstract — quote the original in a code block per
writing-quotation; if the original is in a non-working language, place the translation alongside as a separate paragraph in the same block.
1.2 Body section structure
The body's section structure follows the paper's. If the paper has Section 1 Introduction, Section 2 Method, Section 3 Results, ..., the explainer uses the same order and the same headings.
Add explainer-only sections (e.g. "Strengths of the paper", "Limitations of the paper", "Source list") after the paper's own section structure.
1.3 Bullet lists vs prose
Pick the form by the nature of the content.
- Bullet lists fit enumerations of parallel items — variable lists, definitions of evaluation metrics, table-column descriptions, comparison points between methods, etc. When the content is genuinely list-shaped, the prose form blurs the boundaries between items.
- Prose fits relationships, causal flow, contextual explanation. When the reader needs to understand why items appear together or how they form a single argument, prose is what holds it together.
What ships with it
1 file 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.
- 8d ago First seen · 202 lines · 97 tokens per session scan A dd385a4aef03
paper-details is a skill published in the GitHub repository mathbullet/skills (121 stars, last pushed today), licensed MIT. It adds 97 tokens to every session and 3,074 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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