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MechanismFigures v0.1.0

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@KumarNavish KumarNavish released this 07 Oct 16:16
v0.1.0
1ec08a7

MechanismFigures v0.1.0

An installable Agent Skills-format workflow for mechanism-revealing scientific figures, not a plotting theme or autonomous model.

Install

git clone https://github.com/KumarNavish/MechanismFigures.git
python3 MechanismFigures/tools/install.py

Alternatively unpack the skill ZIP into your host's supported skills directory. The package contains mechanism-figures/SKILL.md, helpers, templates, calibration recipes and licensed images. Python helpers use only the Python 3.9+ standard library. No model API, paid service, browser installation, or telemetry is invoked.

Included

  • A progressive-disclosure, mechanism-to-figure execution workflow with persistent contracts and revision records.
  • Twenty publication-derived calibration recipes; twelve real figure assets from seven references with verified CC BY 4.0 reuse permission. Other figures are linked to their originals, not silently relicensed.
  • A ten-dimensional anchored rubric: weighted score at least 90/100, all dimensions at least 4/5, fidelity 5/5, all ten hard gates passed.
  • Hash-bound evidence/source/output reviews; separate self-review and independent-review statuses.
  • Two original analytical demonstrations with actual first-draft inspection and repair histories.
  • Eight diagnostic four-input task packets, matched evaluation protocol and descriptive benchmark reporter.

Verification

61 engineering regression tests pass locally. The same suite, repository integrity audit, reproducible gallery build, and clean installation checks pass on GitHub Actions with Python 3.9 and 3.12. Ten desktop/mobile/offline browser checks pass for the calibration reader.

These tests verify tooling and recorded review policy, not general scientific/aesthetic quality. Example reviews are creator self-reviews. No cross-agent efficacy study, independently established reference-quality pass rate, or universal publication-quality guarantee is claimed.

The ZIP and its SHA-256 file are attached. Original code/editorial content is MIT licensed; third-party images retain the separate licenses and credits in THIRD_PARTY.md.

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