rt-execution-bridge
Use when an empirical analysis should be RUN and audited, not just advised — DiD, IV, RDD, synthetic control, DML, multiple-testing, sensitivity. Maps the design to the concrete StatsPAI / Stata MCP tools in this environment and reports the fitted, audited number. Defers result placement and house style to the target journal's pack.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill rt-execution-bridge --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Execution Bridge (rt-execution-bridge) Close the last mile: turn "you should use a heterogeneity-robust DiD / weak-IV-robust CI / multiple-testing correction" into an actual fitted, audited estimate. Full map + orchestration spine + validated worked-examples (DiD / IV / RDD / synthetic-control / DML): [`shared-resources/empirical-methods/execution-with-mcp.md`](../../../shared-resources/empirica
What does the rt-execution-bridge skill do?
Use when an empirical analysis should be RUN and audited, not just advised — DiD, IV, RDD, synthetic control, DML, multiple-testing, sensitivity. Maps the design to the concrete StatsPAI / Stata MCP tools in this environment and reports the fitted, audited number. Defers result placement and house style to the target journal's pack.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill rt-execution-bridge --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.