Use when executing and reporting the analysis for a British Journal of Political Science (BJPS) manuscript so it survives expert, double-blind review — honest uncertainty, robustness, and triangulation appropriate to quantitative, experimental, or computational work. Guides analysis norms; it does not fabricate results.
NewMaintained
Automatic
◆Data Analyst pack
Last verified 8/15/2026
What it changes
Passed 11 of 21 test cases with the skill, and 11 of 21 without it.
Without skill50%
With skill50%
Checks it passed that the model alone missed
Requires a single master script to regenerate every table and figure from data
Includes the main estimate magnitude along with confidence or credible intervals
Includes explicit sections for registered versus exploratory analyses and measurement equivalence
2 fixed19 passed either way0 still failing1 broke
Pass-rate lift
0 pp
Tokens
+51%
Agent turns
0%
Response time
-12%
Model gemini-3.6-flashMeasured 8/15/2026v121 of 22 cases passed with skill · 21 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
A test case the skill fixed. Same model, same prompt, with and without the skill.
Prompt
We just completed the main statistical estimation for our comparative political behavior paper intended for BJPS. Format our primary empirical findings into the standard BJPS results delivery template.
What was checked, without and with the skill
Checked
Without skill
With skill
Includes the main estimate magnitude along with confidence or credible intervals
Missed
Passed
Includes explicit sections for registered versus exploratory analyses and measurement equivalence
Missed
Passed
case-01 · gemini-3.6-flash · 8/15/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md107 linessingle file
Data Analysis (bjps-data-analysis)
BJPS reviewers are methodologically sophisticated, and the journal — a DA-RT signatory — expects the
replication data and code behind every reported result to be deposited at acceptance (see
bjps-transparency-and-data). Analyze as if a referee will re-run your code, because the materials
will be public. This skill covers execution and reporting norms; design decisions live in
bjps-research-design.
When to trigger
Running main and supporting analyses; building the results section
A reviewer asked for robustness, heterogeneity, or alternative specifications
Reconciling preregistered vs. exploratory analyses
Making the analysis reproducible before deposit
Analysis norms BJPS expects
Report uncertainty honestly. Confidence/credible intervals, not just stars; the magnitude and
substantive meaning of the estimate, not just its significance.
Robustness that probes, not decorates. Show specifications that could break the result
(alternative measures, samples, estimators, fixed effects), and say what you learn.
Heterogeneity with discipline. Pre-specify subgroups where possible; correct for multiple
comparisons; do not mine for a significant interaction and theorize it post hoc.
Right inference. Cluster at the assignment/sampling level; randomization inference for
experiments; small-cluster corrections (wild-cluster bootstrap) when clusters are few.
Preregistration discipline. Clearly separate registered analyses from exploratory ones;
reconcile deviations from the plan and justify them.
Measurement. Validate constructs; report reliability; show that results are not an artifact of a
coding/scaling choice — especially for cross-national measures that must travel across contexts.
Computational / text-as-data specifics
Document model/version, hyperparameters, seeds, and validation against human-labeled samples.
For topic models/embeddings/LLM pipelines: report stability and a validation step; don't treat
outputs as ground truth.
Cross-national / comparative specifics
Check measurement equivalence across countries/waves before pooling; report whether constructs
mean the same thing across contexts.
Be explicit about what is identified within vs. between units, and where the variation comes from.
Use when running and reporting the analyses for a Comparative Political Studies (CPS) manuscript — estimation, uncertainty, robustness, and multi-method triangulation on comparative data. Sets analysis norms; it does not choose the identification strategy (see cps-research-design).