Single-Experiment Design Review Agent Skill

Rigorously review a single proposed experiment in a grant's Approach section — its rationale, hypothesis, controls (or…

Context cost
2.8k tokensestimated from the bundle, loaded when it triggers
Bundle
1 file · 11.0 kBtext throughout, nothing executable
Licence
not declarednone named by its author
Last change
—no release on file
Servers it uses
Noneruns standalone

What it does

Rigorously review a single proposed experiment in a grant's Approach section — its rationale, hypothesis, controls (or baselines/ablations), variables and confounds, sample size and power, statistical analysis plan, outcomes and interpretation, and feasibility. Works for wet-lab, computational/simulation, clinical, and engineering experiments. Use whenever the user wants one experiment (or one sub-aim's design) evaluated, asks whether an experiment is well designed, mentions controls, confounds, replicates, power analysis, statistical tests, or wants to stress-test the methods a reviewer…

What this skill changes about the agent has not been set out here as a list. Its SKILL.md, shown below, says it in the author’s own words.

productivity

The skill itself

A skill is instructions the model reads, so you can see what you are getting: below is the start of its SKILL.md. The front matter loads with every session, the body loads when the skill triggers, and the whole file comes with the install.

SKILL.md11.0 kB · preview
--- name: grant-approach-experiment ---
6# Single-Experiment Design Review
7
8Under the NIH simplified framework, experimental rigor is the substance of Factor 2 (Rigor and Feasibility); at NSF and DoD it is where methodological reviewers concentrate (verify review-framework specifics against the current FOA and agency guide before relying on them). Reviewers do not fail proposals because the idea is uninteresting nearly as often as because a key experiment cannot answer the question it is posed to answer. This skill audits one experiment at a time, in depth, so those flaws surface before a reviewer finds them.
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10Read _agent/project-config.md first (run grant-setup if missing). The review report goes to _agent/reports/; a power calculation or simulation scripted during the review goes to 02_research_plan/preliminary_data/<aim>/scripts/ with its output in results/ (convention 12). This is the fine-grained companion to grant-approach: use grant-approach for section structure and cross-aim logic, this skill to stress-test an individual experiment. Findings go to _agent/reports/experiment-review_<aim>-<expt>_v<NN>_<YYYY-MM-DD>.md (versioned per the shared schema; <expt> is a short experiment slug so multiple reviews within one aim don't collide); approved revisions flow back into the aim's Approach file per the versioning schema.
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12## Elicit the experiment fully before judging it
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14Do not review from a paragraph of prose alone — prose hides gaps. Draw out, asking only for what is missing:
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16- The question this specific experiment answers, and the hypothesis being tested (or, for a genuinely exploratory experiment, the objective and what will be learned regardless of outcome).
17- Independent variable(s) manipulated; dependent variable(s)/readouts measured; everything held constant.
18- The experimental system (model, cell line, cohort, dataset), groups/conditions, and the comparison being made.
19- Controls planned. Replication structure. Intended analysis and success criterion.
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21Batch all missing-information questions into a single message rather than interrogating across turns; for genuinely minor gaps, proceed with a stated assumption. State back a one-paragraph structured restatement of the experiment and get the user's confirmation. Misunderstanding the design produces useless findings; the restatement is cheap insurance.
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23The dimensions below use wet-lab vocabulary by default, but the logic is general — adapt the terms to the experiment type. For **computational/simulation** work: baselines and ablations play the role of controls, held-out test sets and multiple random seeds address replication and overfitting, and benchmark provenance and code/data availability are the feasibility-and-rigor concern. For **clinical/human-subjects** studies: recruitment feasibility, dropout/attrition, blinding, and inclusion criteria dominate. For **engineering/physical** experiments: reference standards, calibration, tolerances, and test conditions. Ask what kind of experiment it is and map accordingly rather than forcing biological framing.
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This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md1,530 words
Files1
Licencenot declared
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈190
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
2,560
on trigger
The instruction body, read only when the skill fires.
1.4%
of a 200k window
Ten skills this size would take about 14% of the window before you open a file.
050k100k150k200k context window

2.8k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Middling. Fine to keep on in a project where you use it weekly, worth unloading in one where you never do.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

The procedure it runs

The procedure has not been set out here step by step. It is in the body of its SKILL.md: the start of it is shown above, and the whole file comes with the install.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

Its SKILL.md does not declare which tools it asks the agent for, so what it touches is whatever the instructions themselves ask for — read them before you install it.

What it asks for
Writes filesnot declared
Network accessnot declared

This SKILL.md carries no allowed-tools line, so neither is declared. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

1 file, 11.0 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md11.0 kB
What is not in it

No dependencies and nothing executable: a skill is text the agent reads, so the bundle is 1 file you can review in full before installing.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

# Single-Experiment Design Review · 2.8k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/single-experiment-design-review/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/single-experiment-design-review" ] && { [ ! -e .claude/skills/single-experiment-design-review ] || { mv .claude/skills/single-experiment-design-review "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/single-experiment-design-review" .claude/skills/ && echo "Installed .claude/skills/single-experiment-design-review"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add joshua-d-campbell/single-experiment-design-review

Windows PowerShell says 'running scripts is disabled on this system'? Run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or type npx.cmd instead of npx (codex.cmd, gemini.cmd, grok.cmd likewise). PowerShell 7 needs neither. Writes to .claude/skills/single-experiment-design-review/ in the current project. For every project instead, run mkdir -p ~/.claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/single-experiment-design-review/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/single-experiment-design-review" ] && { [ ! -e ~/.claude/skills/single-experiment-design-review ] || { mv ~/.claude/skills/single-experiment-design-review "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/single-experiment-design-review" ~/.claude/skills/ && echo "Installed ~/.claude/skills/single-experiment-design-review" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/single-experiment-design-review/ only after the download succeeds, so files left there by another skill of the same name, or by an older release, do not mix in. A copy already there is moved aside, not deleted, and the line prints where. It appears as grant-approach-experiment in Gemini CLI, Codex, Copilot and Grok (its own name); Claude Code lists it by the folder name, single-experiment-design-review.

Which clients pick it up on their own

A skill is a folder of text. Most of these read a skills folder and pick it up without being told; the rest take the same folder another way — an upload in the app, a parameter on an API call — and then choose it by its description just the same.

Claude Code.claude/skills/
Claude DesktopCustomize › Skills
ChatGPTSkills › Create › Upload
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok Build.grok/skills/
Microsoft CopilotSkills › Upload a skill
PerplexityComputer › Skills › Upload a skill
DeepSeek Harness.dsh/skills/
Zed.agents/skills/
Devin Desktop.devin/skills/
Windsurf (legacy).windsurf/skills/
OpenAI Agents SDKInstructions or sandbox Skills
HTTP / APIa request parameter
This release
Versionnot versioned
Publishedno release date on file
PriceFree
Referencejoshua-d-campbell/single-experiment-design-review

Versions

Its author publishes no version number, so there is nothing here to pin to: what you install is the folder as it stands today. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

Pinning

Nothing to pin to: this skill carries no version number of its own. What you install is what the folder holds on the day you install it.

Reviews

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Anybody with an account, one review each. It carries the version that was current when you wrote it, and the publisher may reply once.

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