Use when defending the research design of an American Journal of Sociology (AJS) manuscript on its own methodological terms — quantitative, comparative-historical, ethnographic, network, or formal. AJS judges each kind of work by the standards of its tradition; the design must support the theoretical claim. Defends the design; it does not run the analysis.
SkillScore91Maintained
Automatic
◆Research pack
Last verified 8/15/2026
What it changes
Passed 20 of 22 test cases with the skill, and 13 of 22 without it.
Without skill59%
With skill91%
Checks it passed that the model alone missed
Recommends running mccrary_test
Includes the section tag 【Verdict】
Includes the section tag 【Tradition】
and 8 more in the full report
7 fixed13 passed either way2 still failing0 broke
Pass-rate lift
+32 pp
Tokens
+36%
Agent turns
0%
Response time
-26%
Model gemini-3.6-flashMeasured 8/15/2026v120 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 7
Prompt
Before issuing final submission advice on an AJS research design review, what specific repository document must be checked for volatile venue rules?
case-19 · 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.md111 linessingle file
Research Design (ajs-research-design)
AJS is method-pluralist: it publishes leading quantitative, comparative-historical, ethnographic,
network, and formal work, and it judges each by the standards of its own tradition. The job here is
to make the design defensible to a generalist, possibly cross-method, double-blind reviewer — and to
show the design actually supports the theoretical claim from ajs-theory-building.
When to trigger
Choosing or justifying the design before data collection or analysis
A reader questioned identification, case selection, sampling, or evidentiary warrant
Aligning the design with the mechanism and observable implications
Mixed-methods work that must defend each component on its own terms
Defend the design (by tradition)
Quantitative / observational
State the estimand and the identifying assumptions plainly; AJS rewards honesty over false
precision. Where the design is descriptive or associational, say so and theorize accordingly.
Justify sample, measurement, and model; pre-empt confounding and selection.
Comparative-historical
Make case selection and the comparative logic explicit (most-similar / most-different,
typical / deviant, scope of the comparison).
Keep a clear evidentiary trail from primary sources to claims; treat sequence and conjuncture as
evidence, not decoration.
Ethnographic / interview
Describe access, site/case selection, duration, and positionality; justify why this case bears
the theoretical weight.
Make the link from fieldnotes/transcripts to claims legible (without exposing informants).
Network / computational
Justify boundary specification, tie definition, and missingness; match the model (e.g., ERGM,
SAOM) to the relational question.
Formal
Tie assumptions to the substantive setting; specify what empirical patterns would corroborate or
challenge the model.
Use when defending the research design of an American Journal of Political Science (AJPS) manuscript — causal identification for observational work, experimental and survey-experimental design, formal-empirical linkage, or case-based inference. AJPS reviewers are quantitatively demanding, so identification must license the claim being made. Strengthens the design; it does not write code.