Skills · Awesome Journal Skills (AJS)
rt-execution-bridge
Runs and audits the empirical analysis rather than just advising — maps a DiD/IV/RDD/synthetic-control/DML design to the concrete StatsPAI / Stata MCP tools in the environment and reports the fitted, audited number.
Where it sits
left: what it builds on · right: what builds on it · pale: exampleContributed by Bryce Wang
How studies reach it
No published study reaches it yet.
Disciplines it reaches
No study reaches it yet.
Solid: published studies. Light: examples.
Computed from the records on this site: what each study, template and specialist names as used, which study extends which, and who contributed what. 0 studies in total.
Provenance
- Project
- Awesome Journal Skills (AJS)
- Maintained by
- Bryce Wang (Stanford REAP / CoPaper.AI)
- Licence
- MIT · can be redistributed
- Source file
- brycewang-stanford/Awesome-Journal-Skills/blob/main/Research-Toolkit-Skills/skills/rt-execution-bridge/SKILL.md
- Identifier
- awesome-journal-skills/rt-execution-bridge
Use it
e2er skills install awesome-journal-skillsThe command is on the development branch of E2ER.
Used by
No E2ER specialist loads this skill by default. Once installed, a template can assign it to a specialist.
Evaluations
PlannedNo evaluation record yet. An evaluation shows where a skill breaks before others rely on it.
Evaluate this skillDescription
Data model- Discipline
- General
- Method family
- not specified
- Design
- not specified
- Research stage
- Data analysisCode generation
- Contributors
- Bryce Wang
- Usage
- not used in published research yet
- Source
- RISE skill catalogue · awesome-journal-skills · @4c17bae
- Record
- skill:awesome-journal-skills/rt-execution-bridge · JSON
Solid tags are declared by the source or mapped from its terms; dashed tags are inferred by a published rule. Hover a tag for its provenance.