io-research-design — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited io-research-design (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
IO accepts quantitative, formal, and qualitative IR work but is demanding about each. The design must credibly connect the IR theory (io-theory-building) to evidence at or across the international level, and rule out the strongest rival international explanation. This skill is mode-aware: pick the section that matches your work.
io-literature-positioningsub-state, transnational) and why it matches the theory. Many IR mistakes are unit/level mistakes.
(ignorability, parallel trends, exclusion, continuity); defend them, don't assert them.
multiway, or use AME/network models); spatial and temporal dependence in TSCS; selection into alliances/treaties/conflict; reverse causation (does the institution cause the behavior or vice versa).
IV with credible exclusion at the international level, RDD where thresholds exist, matching/weighting with balance + sensitivity, gravity/PPML for trade flows.
across dyads or institutions) — say what the case is a case of in IR terms.
would have disconfirmed the international mechanism.
citation now (QDR; see io-transparency-and-data-policy).
state behavior is a real inferential leap — caveat it.
For the single strongest rival international explanation, write one sentence: "If the rival were true rather than my argument, the international data/cases would look like ___; instead they look like ___." If you cannot, the design does not yet identify the IR contribution.
Claim: ratifying an international monitoring treaty raises later compliance. The naive cross-section confounds the effect with selection into membership — states that mean to comply ratify. An IO-credible design exploits variation in ratification timing: among eventual ratifiers, treat the staggered timing as identification with a modern staggered DID/event-study estimator (not naive TWFE) and report pre-trends. The adjudication sentence: if selection drove compliance, the gain would appear before ratification; instead it appears only after and tracks monitoring intensity. A sensitivity check then asks how strong an unobserved confounder must be to overturn it (say, twice the observed regime-type effect — illustrative). Timing-based identification, a rival-ruling counterfactual, and a sensitivity bound convert an association into an IR causal claim at IO.
| Threat | Where it appears | Design answer |
|---|---|---|
| Selection into treaty/alliance/IO membership | compliance, cooperation studies | ratification-timing, instrument, or selection model + sensitivity |
| Dyadic / network non-independence | any dyad-level outcome | multiway/dyadic-robust SEs or AME/latent-space models |
Estimate and audit the design, don't only describe it. Full map: execution-with-mcp. International Organization is IR — country/dyad panels with difficult identification; foreground the source of variation and robustness to alternative explanations.
detect_design → recommend → fit with as_handle=true → audit_result.callaway_santanna / sun_abraham +bacon_decomposition + honest_did_from_result); IV (effective_f_test + anderson_rubin_ci); RDD (rdrobust + mccrary_test).
romano_wolf for many-outcomefamily-wise control, and mediate for mediation (not naive controlling-away).
oster_delta / sensemakr for observational claims.Report the effect size in interpretable units; route the full battery to the appendix/supplement. A run end-to-end (synthetic data, real returns) is in the JF execution walkthrough.
【Mode】quant-causal / qualitative / experiment / formal-empirical
【Level of analysis】unit + why it matches the IR theory
【Estimand or claim】what is being identified/shown
【Key assumption(s)】and how each is defended (incl. dyadic/TSCS dependence)
【Rival ruled out】the adjudication sentence
【Robustness/sensitivity / proof appendix】planned
【Next】io-data-analysis../../resources/external_tools.md — dyadic/network/gravity packages and CAQDAS for qualitative IR../../resources/official-source-map.md — formal-proof and quantitative-result verification policy~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.