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experiment-plan

experiment-plan is a skill for Claude Code from AutoConference/AutoConference-skill. It costs 80 tokens per session (2,209 once invoked), scanned A, a copy of experiment-plan, Apache-2.0.

A research experiment plan that connects each paper claim to evidence, comparisons, tests, and an execution order. It is aimed at validating a proposed method rather than collecting an unfocused list of benchmarks.

In plain words
What is it for?
Use it to design evaluation protocols, ablation matrices, baseline comparisons, run order, and compute planning for a research paper.
Why use it?
It reduces wasted experiments by identifying which tests are necessary to support the main claims and which are optional.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is - **[Output Versioning Protocol](../shared-references/output-versioning.md)** — write timestamped file first, then copy to fixed name.

not rated 13repo 4d ago A scan 80 tokens copy · 100% Apache-2.0

Good fit Use it to design evaluation protocols, ablation matrices, baseline comparisons, run order, and compute planning for a research paper.

Compare 6 skills from other repositories ↓
View source ↗ AutoConference/AutoConference-skill
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/AutoConference/AutoConference-skill
agentmods
npx agentmods add skills/autoconference/autoconference-skill/experiment-plan

Made for: Claude Code.

Wrote 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.

agentmods badge for experiment-plan

README.md
[![agentmods](https://agentmods.dev/badge/skills/autoconference/autoconference-skill/experiment-plan/github.svg)](https://agentmods.dev/skills/autoconference/autoconference-skill/experiment-plan)
Your own site
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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.

agentmods 80×15 button for experiment-plan

Your own site · 80×15
<a href="https://agentmods.dev/skills/autoconference/autoconference-skill/experiment-plan"><img src="https://agentmods.dev/badge/skills/autoconference/autoconference-skill/experiment-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,209 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00080 $0.02209
Opus 5.5 $0.00032 $0.00884
Sonnet 5.5 $0.00016 $0.00442
Haiku 4.5 $0.00008 $0.00221

Measured 1mo ago against content hash c5b53692ff95, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

experiment-plan 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.

Origin

This is a copy

100% identical to experiment-plan — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/aris/experiment-plan/SKILL.md · 250 lines

How it starts

The opening of the file, as written. The whole thing — 250 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Experiment Plan: Claim-Driven, Paper-Oriented Validation

Refine and concretize: $ARGUMENTS

Overview

Use this skill after the method is stable enough that the next question becomes: what exact experiments should we run, in what order, to defend the paper? If the user wants the full chain in one request, prefer /research-refine-pipeline.

The goal is not to generate a giant benchmark wishlist. The goal is to turn a proposal into a claim -> evidence -> run order roadmap that supports four things:

  1. the method actually solves the anchored problem
  2. the dominant contribution is real and focused
  3. the method is elegant enough that extra complexity is unnecessary
  4. any frontier-model-era component is genuinely useful, not decorative

Constants

  • OUTPUT_DIR = refine-logs/ — Default destination for experiment planning artifacts.
  • MAX_PRIMARY_CLAIMS = 2 — Prefer one dominant claim plus one supporting claim.
  • MAX_CORE_BLOCKS = 5 — Keep the must-run experimental story compact.
  • MAX_BASELINE_FAMILIES = 3 — Prefer a few strong baselines over many weak ones.
  • DEFAULT_SEEDS = 3 — Use 3 seeds when stochastic variance matters and budget allows.

Workflow

Phase 0: Load the Proposal Context

Read the most relevant existing files first if they exist:

  • refine-logs/FINAL_PROPOSAL.md
  • refine-logs/REVIEW_SUMMARY.md
  • refine-logs/REFINEMENT_REPORT.md

Extract:

  • Problem Anchor
  • Dominant contribution
  • Optional supporting contribution
  • Critical reviewer concerns
  • Data / compute / timeline constraints
  • Which frontier primitive is central, if any

If these files do not exist, derive the same information from the user's prompt.

Phase 1: Freeze the Paper Claims

Before proposing experiments, write down the claims that must be defended.

Use this structure:

  • Primary claim: the main mechanism-level contribution
  • Supporting claim: optional, only if it directly strengthens the main paper story
  • Anti-claim to rule out: e.g. "the gain only comes from more parameters," "the gain only comes from a larger search space," or "the modern component is just decoration"
  • Minimum convincing evidence: what would make each claim believable to a strong reviewer?

Read the full file on GitHub · 250 lines

Changes

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.

  1. 1mo ago First seen · 250 lines · 80 tokens per session scan A c5b53692ff95

Subscribe to this mod's changes

experiment-plan is a skill published in the GitHub repository AutoConference/AutoConference-skill (13 stars, last pushed 4d ago), licensed Apache-2.0. It adds 80 tokens to every session and 2,209 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to experiment-plan, differing in 0 lines, and is treated as a copy.

PlanningResearch
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