Skip to content

Repository files navigation

JEPA Skills

A reusable skill package for Claude Code, Codex, and similar coding/research agents focused on JEPA research workflows.

What this project provides

  • jepa-research/SKILL.md: JEPA research skill definition (triggering + workflow, 4 modes).
  • metadata/: structured indexes (papers, code, evidence) with 71% long-tail coverage.
  • scripts/: corpus organization, metadata build, evidence validation, and annotation scripts.
  • eval/: 40-prompt benchmark suite with scoring rubric and 5-version comparison history.
  • docs/: roadmap, execution tracker, evidence schema, paper-code linking policy, release workflow.
  • CLAUDE.md: project rules for Claude Code agents working in this repo.

What this project does not bundle by default

  • Full paper PDFs and full third-party codebases should usually stay local.
  • For open-source publishing, share metadata + scripts; fetch source artifacts on demand.

Repository layout

.
+-- jepa-research/
|   +-- SKILL.md
|   +-- references/
|   `-- scripts/
+-- metadata/
+-- scripts/
`-- corpus/                   # local cache; large files ignored by default

Quick start

  1. Put your local paper/code assets under corpus/ (optional for public repo users).
  2. Build a shareable paper catalog:
python scripts/build_paper_catalog.py --input metadata/papers_index.csv --output metadata/paper_catalog.csv
  1. Use the skill:
    • Ask the agent about JEPA paper comparison, reproduction, debugging, intro drafting, and citations.
    • The skill expects evidence-style answers tied to metadata records.

Environment and migration notes

  • The Python scripts in this repo use the standard library only. There is currently no requirements.txt or pyproject.toml.
  • Validate on Python 3.11+. This repo was checked successfully with Python 3.13.5.
  • Run commands from the repo root so relative paths resolve correctly.
  • The current corpus layout expected by metadata and evidence files is:
    • corpus/papers/all/
    • corpus/code/archives/
  • The optional import script scripts/organize_jepa_corpus.ps1 can ingest raw assets from:
    • JEPA-Papers/
    • JEPA-Papers/awesome-jepa/
    • JEPA-CodeBase/
  • After moving the repo to another machine, the recommended sanity check is:
python scripts/build_paper_catalog.py --input metadata/papers_index.csv --output metadata/paper_catalog.csv
python scripts/validate_evidence_index.py --input metadata/evidence_index.csv --check-paths --json eval/results/evidence_index_validation.json
python scripts/check_metadata_completeness.py --input metadata/paper_catalog.csv --json eval/results/metadata_completeness_report.json

Skill capabilities (v1.3.0)

All 4 modes score 100% on the 40-prompt eval benchmark:

Mode Factual Citation Key Metric
Research Q&A 100% 100% —
Reproduction Plan 100% 100% Executability 100%
Debug Triage 100% 100% Debug Hit 100%
Writing/Citation 100% 100% —
Hallucination rate 0.0%

See eval/results/v1_3_0_benchmark_comparison.md for the full 5-version comparison from v1.0.0 to v1.3.0.

Open-source readiness

This repo is ready to open-source as a metadata-and-workflow package. Third-party paper PDFs and code archives are excluded from Git by .gitignore.

Release gates (all passing for v1.3.0):

  1. production evidence schema documented ✅
  2. evidence_index.csv with real data ✅
  3. validation scripts for evidence and metadata completeness ✅
  4. documented eval workflow that another contributor can rerun ✅

Sanity check after cloning:

python scripts/build_paper_catalog.py --input metadata/papers_index.csv --output metadata/paper_catalog.csv
python scripts/annotate_long_tail.py --input metadata/paper_catalog.csv --output metadata/paper_catalog.csv
python scripts/validate_evidence_index.py --input metadata/evidence_index.csv --check-paths --json eval/results/evidence_index_validation.json
python scripts/check_metadata_completeness.py --input metadata/paper_catalog.csv --json eval/results/metadata_completeness_report.json

Open-source release checklist

  1. Keep .gitignore defaults for corpus/papers/all and corpus/code/archives ✅
  2. Keep metadata CSVs and templates ✅
  3. MIT license included ✅
  4. Users are responsible for third-party paper/code licenses ✅

About

Reusable Claude Code skill for JEPA (Joint Embedding Predictive Architecture) research — Q&A, reproduction, debugging, and writing with traceable evidence. 40-prompt benchmark at 100% across all metrics.

Resources

Contributing

Stars

4 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages