jape-contribution-framing — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited jape-contribution-framing (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.
JAE rewards a contribution that is an application on real data with replicable results: here is a substantive question, here is a credible empirical strategy applied to real data, here is what we find, and every number can be regenerated from the data and code we deposit. Acceptable types:
Pure theoretical novelty ("we prove a new asymptotic result") is not the JAE contribution; if you have method development, frame the real-data demonstration as the payoff.
Applied-econometrics referees punish over-claiming. The contribution must not exceed what the design and data support — distinguish association from causal effect, note external-validity limits, and let replicability carry weight: a modest reproducible finding beats an overclaimed fragile one.
The contribution must compress into a summary of ≤ 100 words containing no citations, understandable on its own (see jape-writing-style). Draft the one-sentence contribution first, expand into the summary, then back-check against the results.
Before any referee sees the paper, the editorial screen looks for the venue's identity markers. Put them where they are found fast:
| Signal | Where it must appear | Risk if missing |
|---|---|---|
| Real data named (source, span, frequency, N) | First two pages | Read as a theory paper mis-sent to an applied journal |
| Econometric lesson (when/why the method matters here) | Contribution paragraph | "Estimator demo without an applied payoff" |
| Replication commitment (deposit to the JAE Data Archive) | Intro or data section | Doubt about reproducibility — fatal at this venue |
| Claim calibrated to design (causal vs. associational) | Contribution paragraph | Over-claiming flag from applied-econometrics referees |
Illustrative numbers only. Draft claim: "We show import prices respond incompletely to exchange rates." Too thin for JAE. Reframed: "Using monthly import-price micro data on 1,900 product lines (2002–2023), we estimate 12-month pass-through of 0.31 (HAC s.e. 0.06) — roughly half the aggregate consensus — and show the gap closes once invoicing-currency composition is held fixed; all series and programs will be deposited in the JAE Data Archive." This names the data, the inference, the quantitative finding, the econometric lesson (aggregation bias in pass-through regressions), and the replication hook — the elements a JAE contribution paragraph carries.
Hedged from public JAE issues rather than internal data: accepted papers tend to state the contribution within the first two pages, quantify the headline estimate with its standard error early, and spend a sentence on portability — why the approach generalizes past this application. Confirm current scope wording against the journal's author guidelines.
【Type】new finding / method application / replication
【Claim】associational / causal — matches design? [Y/N]
【Replicable hook】stated? [Y/N]
【Summary fit】≤100 words, no citations, self-contained? [Y/N]
【Lesson】econometric takeaway travels beyond this dataset? [Y/N]../../resources/official-source-map.md — summary cap and scope sources~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.