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 gabrielmoreira/agent-skills-mirror --skill oral-paper-skillgit clone --depth 1 https://github.com/gabrielmoreira/agent-skills-mirrorWrote 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/gabrielmoreira/agent-skills-mirror/oral-paper-skill)<a href="https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/oral-paper-skill"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/oral-paper-skill/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/gabrielmoreira/agent-skills-mirror/oral-paper-skill"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/oral-paper-skill.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 | $0.00068 | $0.01394 |
| Opus 5.5 | $0.00027 | $0.00558 |
| Sonnet 5.5 | $0.00014 | $0.00279 |
| Haiku 4.5 | $0.00007 | $0.00139 |
Grade A, and why
oral-paper-skill 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 28d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Oral Paper Skill
Turn useful practices from exemplary papers into concrete revisions and focused learning. Offer two services: compare and improve a manuscript, or learn and reflect on a practice. Preserve the author's research purpose and judgment.
The current knowledge base includes semantic extraction of 883 abstracts from 884 official event records, source checks, and cross-paper synthesis. It is abstract-level evidence, not 883 full-paper readings or an explanation of Oral selection. For provenance, read sources and reading levels.
Start from the author's purpose
Identify the requested artifact, contribution type, stage, and relevant constraints. Use the supplied draft, results, and examples before asking for more. Ask only when missing information would materially change the advice or authorization.
Several coherent contributions are allowed. Missing evidence in an early idea differs from evidence contradicting a result claim. Do not turn a writing or learning request into an automatic decision to abandon research.
Choose a relevant practice and example
Read abstract-derived practices and examples when applying the distilled knowledge. Select only the practices useful for this request; do not run every paper through all seven.
- Specify the research tension. Identify an unmet requirement or an observation that makes the question worth investigating. Do not manufacture a prior-work failure.
- State the contribution delta. Name the changed output, operation, representation, assumption, or enabled activity. A method name and “novel” do not explain the difference.
- Match evidence to the claim. Identify the measured or proved property. Keep attempts distinct from success, a proxy from the whole capability, and proposed evaluation from reported outcomes.
- Choose a meaningful comparison. Explain what decision it resolves, what stays fixed, and what changes. For efficiency, identify the actual resource unit and accounting boundary; active parameters, tokens, latency, memory and total cost are different quantities.
- Keep conditions beside conclusions. Preserve the model class, quantifier, guarantee regime, comparator and numerical convention that give the result its meaning.
- Explain what the resource enables. Connect contents or interfaces to a research activity. Distinguish intended uses, demonstrated uses and release commitments.
- Extract a bounded lesson. Explain what readers can reconsider or investigate, separating observation, interpretation and a proposed action. State what would limit transfer.
What ships with it
5 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.
- 28d ago First seen · 73 lines · 68 tokens per session scan A 224bc8fe3119
oral-paper-skill is a skill published in the GitHub repository gabrielmoreira/agent-skills-mirror (19 stars, last pushed yesterday), licensed MIT. It adds 68 tokens to every session and 1,394 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-20.
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