preregister

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• SKILL.md

SKILL.md (first lines)

# Preregistration

This file is the canonical Empirical Workflow Kit implementation. Runtime views
defined in `workflow.manifest.yaml` link here; edit only the canonical tree.

Resolve `<skills_root>` from `workflow.manifest.yaml:canonical_source.skills_root`
before using a path below.

Adapted from Lan E. Luo's `claude-academic-workflow` preregistration skill at
commit `8958cc246e65cdf7c36604f397a1c1719b7e2c14`. See
`THIRD_PARTY_NOTICES.md`.

A preregistration is a written commitment to hypotheses, design, and analysis made before the data
exist or before the realized focal outcome has been seen. It separates confirmatory from
exploratory work and closes off p-hacking, HARKing, and forking paths. This skill writes the
document; the user submits it. To critique a preregistration that already exists, use the
council skill; this one drafts.

Structure and the MUST/SHOULD/MAY taxonomy descend from
`pedrohcgs/claude-code-my-workflow`, as recorded by the upstream attribution.

The durable source of preregistration state is the project record initialized
from `<skills_root>/empirical-workflow/templates/preregistration-template.yaml`.
Registry-form prose is an export from that record. Claim revisions and gate
identifiers must match the project governance registry.

For research organization, economic meaning, contribution, and behavioral claims,
read `../empirical-workflow/references/research-writing.md` before synthesis or
drafting. Apply the relevant evidence-strategy boundary; do not turn the
operation's output format into a mandatory manuscript structure.

## The refusal gate

Check this before reading anything else, and check it again if new information arrives mid-draft.
Retrospective preregistration is prohibited.

Refuse if the description contains realized results: "we found", "the estimate is", "p =", "the
effect was significant", "condition A scored higher", a coefficient, a sample mean, or a figure
of results. Say plainly that a preregistration is forward-looking, that writing one now would
misrepresent the analysis order, and offer instead to write it up as an exploratory analysis or a
methods section, clearly labeled as such.

Refuse in the same way if the user has run the focal analysis on data they hold, even without
stating the numbers. The gate is about analysis order, not about whether numbers appear in the
prompt. Ask directly: has the focal outcome been analyzed on these data yet? If the answer is yes
or evasive, do not write a preregistration.

Two things are not refusals. Preregistering a new confirmatory test on data the user holds but
has not examined for that outcome is legitimate; say so in the document under existing data, and
state what has already been seen. And a purely exploratory study does not need a preregistration
at all, it needs honest labeling, so offer the OSF exploratory variant instead.

## Arguments

- `--style aspredicted|osf|aea-rct`: override the registry choice.
- `--input <path>`: a study spec to read (Markdown draft, Notion export, planning doc section).
- `--format md|tex`: output format, default `md`.
- `--no-verify`: skip the citation checks in phase 5.

## Phase 1. Read the inputs

With `--input`, read the spec and pull out: research question, hypotheses, data source, design,
conditions, sample, primary analysis, any stated `paper_type`.

Without it, ask for a one-to-three paragraph description of the study. If no description comes
back, stop and ask again. Do not write a document made entirely of placeholders.

If the description has no directional hypothesis, ask once. Do not invent a direction.

## Phase 2. Pick the registry

| Signal | Style |
|---|---|
| Online vignette, MTurk or Prolific study, short lab experiment, 1 to 3 DVs | `aspredicted` |
| Conjoint, eye-tracking, multi-DV survey experiment, complex or stratified sampling | `osf` |
| Steering calibration study (confirmatory steering work) | `osf` |
| Field experiment or RCT (livestream pilot, retailer pilot, app A/B test) | `aea-rct` |
| Observational confirmatory analysis | `osf`, preanalysis-plan variant |
| Ambiguous | `aspredicted` |

The 1 to 3 DVs cut is a rule of thumb for form length, not a registry rule.

Steering calibration studies prespecify the sweep protocol, the quality gate, and the audit
battery, plus the primary construct instrument.

AEA RCT registration is required for field experiments at AEA journals (lab experiments are
exempt) and accepted by Marketing Science and Management Science; either OSF or AEA works for
those two. For any other UTD 24 or FT 50 target (the IS, OM, management, accounting, and finance
journals in `<skills_root>/literature-review/references/journal-scope.md`), read the current
author guidelines before choosing a registry, record the access date, and do not infer one
journal's policy from another's. Clinical trials (ClinicalTrials.gov, ISRCTN) belong in their own
registries and are out of scope here. PROSPERO takes only reviews with health outcomes, so it is
not a destination for a business-school meta-analysis.

## Phase 3. Write the document

Every field gets one flag:

- MUST, the registry will not accept the submission without it
- SHOULD, reviewers and editors expect it even though the form does not force it
- MAY, include when relevant

For any MUST the input did not supply, write `[CLARIFY: <specific question>]`. Never fill a MUST
with plausible-sounding invention.

Common header for all three styles: title, authors, date, version (`v0.1` draft, `v1.0` at
upload), target journal, and a pointer back to the source spec if `--input` was given.

### AsPredicted, the nine questions

1. Have any data been collected for this study already? (MUST, and answer it honestly)
2. What is the main question or hypothesis? (MUST, directional)
3. Key dependent variable(s) and exactly how they are measured (MUST)
4. How many and which conditions participants are assigned to (MUST)
5. Exactly which analyses will test the main hypothesis (MUST, name the estimator)
6. Outliers and exclusions, decided now (MUST)
7. Sample size and stopping rule (MUST, see below)
8. Anything else (SHOULD, put the falsification criterion and power basis here)
9. Name of the study, not the paper (MUST)

From bobbyZhong10/empirical-workflow-kit, MIT.

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