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 sidiangongyuan/codex-skills-library --skill experiment-plannergit clone --depth 1 https://github.com/sidiangongyuan/codex-skills-libraryWrote 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/sidiangongyuan/codex-skills-library/experiment-planner)<a href="https://agentmods.dev/skills/sidiangongyuan/codex-skills-library/experiment-planner"><img src="https://agentmods.dev/badge/skills/sidiangongyuan/codex-skills-library/experiment-planner/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/sidiangongyuan/codex-skills-library/experiment-planner"><img src="https://agentmods.dev/badge/skills/sidiangongyuan/codex-skills-library/experiment-planner.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 | $0.00045 | $0.02646 |
| Opus 5.5 | $0.00018 | $0.01058 |
| Sonnet 5.5 | $0.00009 | $0.00529 |
| Haiku 4.5 | $0.00005 | $0.00265 |
Grade A, and why
experiment-planner 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 1mo 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 — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Experiment Planner
Overview
Use this skill when the user needs to explore a research idea, continue an authorized experiment workflow, or accept and interpret results. It turns claims into a testable story and experiment plan. It is an adapter over existing research-agent ideas, not a replacement for the user's writing, review, rebuttal, figure, evidence, or GitHub release skills.
Core Boundaries
- Default domain: general deep learning and computer science research. Adapt to collaborative perception, 3D perception, or autonomous driving only when the task context calls for it.
- For discussion-only planning, keep output in chat unless the user asks for a
saved artifact. When the user asks to implement or run experiments in a
repository, persist the pre-run result contract: update the paper's final
LaTeX tables when a manuscript is in scope; otherwise update the existing
experiment-planning document or create
experiment-plan.mdat the repository root. - Do not launch long experiments, deploy GPU jobs, modify code, or retry failed runs unless the user explicitly asks for execution or a still-valid approval covers the ordinary continuation. A bounded same-config recovery stays within that approval; do not silently expand its scope.
- Do not replace
paper-writing,paper-review-panel,rebuttal-response-skills,paper-visual-craft, orgithub-project-release; hand off to them only after the research plan or results are ready. - Treat external projects as references, not installed dependencies. Read
references/source-map.mdbefore discussing provenance or upgrading this skill from upstream sources. - During approved execution, a still-valid earlier user authorization covers ordinary implementation, local bug fixes, queueing in-scope runs, and evaluation. It does not authorize a new experiment family, dataset, seed policy, or paper-only TODO; those remain explicit opt-ins.
Entry Modes
Choose the mode that matches the current request:
What ships with it
4 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.
- 1mo ago Changed baa6e576ba32
- 1mo ago Changed · +93 lines · -3 tokens per session 0c1281e660c6
- 1mo ago First seen · 140 lines · 48 tokens per session scan A 121b1ff348e2
experiment-planner is a skill published in the GitHub repository sidiangongyuan/codex-skills-library (24 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 2,646 once invoked, about $0.0002 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 2026-08-31.
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zeroplot
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A tool for simulating peer review of a research paper from the reviewer’s point of view. Peer review is the process in which experts assess a paper before publication.
nature-ref-verifier
A reference-checking workflow that compares bibliographic details across multiple sources. Bibliographic details include authors, title, year, volume, issue, pages, and DOI, the persistent identifier for a research publication.
nature-paper2word
A document conversion workflow that turns an academic Markdown manuscript into a Word .docx file. It supports specified academic formatting, equations, tables, references, cross-references, and export checks.
nature-statistics
A guide for checking or writing how statistical analyses are reported in scientific papers submitted to Nature or similar high-impact journals.
nature-paper-trans
A workflow for translating selected pages or a complete English research-paper PDF into a simplified-Chinese, image-based PDF. bioRxiv is not mentioned in the provided details; the workflow applies to research-paper PDFs generally.