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Subagent Driven Analysis Agent Skill

Use when executing a pre-registered analysis plan with mostly independent steps in the current session

4k tokens
context cost
the whole folder, loaded on every use
4
files
instructions only
0
copies elsewhere
how many repositories repackaged it
280
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/K-Dense-AI/science-superpowers --skill subagent-driven-analysis

The instruction itself

9 sections, as written by the author

Subagent-Driven Analysis

Execute a pre-registered analysis plan by dispatching a fresh subagent per analysis step, with two-stage review after each: protocol-compliance review first (did it run exactly what was pre-registered, nothing more), then statistical-rigor review (assumptions, leakage, correctness, reproducibility).

Why subagents: You delegate steps to specialized agents with isolated context. By precisely crafting their instructions, you keep them focused and prevent them from improvising analyses you didn't pre-register. They never inherit your session's history — you construct exactly what they need. This also preserves your own context for coordination.

Core principle: Fresh subagent per step + two-stage review (protocol then rigor) = trustworthy, reproducible results.

Continuous execution: Do not pause to check in between steps. Execute the whole plan. The only reasons to stop: a BLOCKED status you cannot resolve, an anomaly that needs science-superpowers:investigating-anomalous-results, a genuine ambiguity, or all steps complete.

Prerequisite

The analysis plan MUST be pre-registered and frozen (science-superpowers:preregistering-analysis) before any step runs. If it is not frozen, stop and pre-register first. Executing before freezing turns the whole thing exploratory.

When to Use

digraph when_to_use {
    "Pre-registered plan?" [shape=diamond];
    "Steps mostly independent?" [shape=diamond];
    "Stay in this session?" [shape=diamond];
    "subagent-driven-analysis" [shape=box];
    "executing-analysis" [shape=box];
    "Pre-register first" [shape=box];

    "Pre-registered plan?" -> "Steps mostly independent?" [label="yes"];
    "Pre-registered plan?" -> "Pre-register first" [label="no"];
    "Steps mostly independent?" -> "Stay in this session?" [label="yes"];
    "Stay in this session?" -> "subagent-driven-analysis" [label="yes"];
    "Stay in this session?" -> "executing-analysis" [label="no - parallel session"];
}

The Process

digraph process {
    rankdir=TB;

    "Set up reproducible workspace" [shape=box];
    "Read plan + frozen prereg, extract all steps, create TodoWrite" [shape=box];
    "Dispatch analyst subagent (./analyst-prompt.md)" [shape=box];
    "Analyst asks questions?" [shape=diamond];
    "Answer, provide context" [shape=box];
    "Analyst runs step, validates, commits, self-reviews" [shape=box];
    "Dispatch protocol-compliance reviewer (./protocol-compliance-reviewer-prompt.md)" [shape=box];
    "Ran exactly the pre-registered analysis?" [shape=diamond];
    "Analyst fixes deviations" [shape=box];
    "Dispatch rigor reviewer (./rigor-reviewer-prompt.md)" [shape=box];
    "Rigor reviewer approves?" [shape=diamond];
    "Analyst fixes rigor issues" [shape=box];
    "Mark step complete" [shape=box];
    "More steps?" [shape=diamond];
    "Use requesting-red-team-review on whole result" [shape=box style=filled fillcolor=lightgreen];
    "Use reporting-and-archiving-findings" [shape=box style=filled fillcolor=lightgreen];

    "Set up reproducible workspace" -> "Read plan + frozen prereg, extract all steps, create TodoWrite";
    "Read plan + frozen prereg, extract all steps, create TodoWrite" -> "Dispatch analyst subagent (./analyst-prompt.md)";
    "Dispatch analyst subagent (./analyst-prompt.md)" -> "Analyst asks questions?";
    "Analyst asks questions?" -> "Answer, provide context" [label="yes"];
    "Answer, provide context" -> "Dispatch analyst subagent (./analyst-prompt.md)";
    "Analyst asks questions?" -> "Analyst runs step, validates, commits, self-reviews" [label="no"];
    "Analyst runs step, validates, commits, self-reviews" -> "Dispatch protocol-compliance reviewer (./protocol-compliance-reviewer-prompt.md)";
    "Dispatch protocol-compliance reviewer (./protocol-compliance-reviewer-prompt.md)" -> "Ran exactly the pre-registered analysis?";
    "Ran exactly the pre-registered analysis?" -> "Analyst fixes deviations" [label="no"];
    "Analyst fixes deviations" -> "Dispatch protocol-compliance reviewer (./protocol-compliance-reviewer-prompt.md)" [label="re-review"];
    "Ran exactly the pre-registered analysis?" -> "Dispatch rigor reviewer (./rigor-reviewer-prompt.md)" [label="yes"];
    "Dispatch rigor reviewer (./rigor-reviewer-prompt.md)" -> "Rigor reviewer approves?";
    "Rigor reviewer approves?" -> "Analyst fixes rigor issues" [label="no"];
    "Analyst fixes rigor issues" -> "Dispatch rigor reviewer (./rigor-reviewer-prompt.md)" [label="re-review"];
    "Rigor reviewer approves?" -> "Mark step complete" [label="yes"];
    "Mark step complete" -> "More steps?";
    "More steps?" -> "Dispatch analyst subagent (./analyst-prompt.md)" [label="yes"];
    "More steps?" -> "Use requesting-red-team-review on whole result" [label="no"];
    "Use requesting-red-team-review on whole result" -> "Use reporting-and-archiving-findings";
}

Model Selection

Use the least powerful model that can handle each role.

  • Mechanical steps (load data, apply a fixed transform, produce a planned figure): fast, cheap model.
  • Integration/judgment steps (fitting the primary model, handling missingness per plan): standard model.
  • Rigor review and anomaly judgment: most capable model.

Handling Analyst Status

DONE: Proceed to protocol-compliance review.

DONE_WITH_CONCERNS: Read the concerns. If about correctness or an unexpected data issue, address before review (may need science-superpowers:investigating-anomalous-results). If an observation ("this file is getting large"), note and proceed.

NEEDS_CONTEXT: Provide the missing information and re-dispatch.

BLOCKED: Assess. Context problem → provide more and re-dispatch. Needs more reasoning → more capable model. Step too large → split. Plan itself is wrong → escalate to your human partner. A wrong plan may require re-opening the pre-registration, which must be documented as a deviation.

Never silently let a subagent change the registered analysis to make a step "work." A deviation is documented and renders that analysis exploratory.

Prompt Templates

  • ./analyst-prompt.md — dispatch the analyst subagent
  • ./protocol-compliance-reviewer-prompt.md — did it match the pre-registration?
  • ./rigor-reviewer-prompt.md — is the statistics correct, reproducible, leak-free?

Red Flags

Never:

  • Execute before the pre-registration is frozen
  • Skip either review (protocol OR rigor)
  • Let a subagent add an unregistered analysis and report it as confirmatory
  • Run rigor review before protocol compliance is green (wrong order)
  • Accept a silently dropped outlier or changed cutoff (route to anomaly investigation instead)
  • Dispatch multiple analyst subagents on the same artifacts in parallel (conflicts)
  • Make the subagent read the whole plan (provide the step's full text + the relevant pre-registration excerpt)

If a reviewer finds issues: the same analyst subagent fixes them, then the reviewer reviews again. Repeat until approved.

Integration

Required workflow skills:

  • science-superpowers:setting-up-reproducible-analysis — isolated, seeded, reproducible workspace (run first)
  • science-superpowers:preregistering-analysis — must be frozen before execution
  • science-superpowers:investigating-anomalous-results — when a step's output is surprising or impossible
  • science-superpowers:requesting-red-team-review — adversarial review of the whole result
  • science-superpowers:reporting-and-archiving-findings — after all steps complete

Subagents should use:

  • science-superpowers:verifying-results-before-claiming — before any subagent reports a step as done

Alternative:

  • science-superpowers:executing-analysis — inline execution for harnesses without subagents

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How to use it

Copy the folder

Take k-dense-ai/subagent-driven-analysis from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

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