---
name: Chemistry Ranked Entities And Property Curves
slug: chemistry-ranked-entities-and-property-curves
category: Data
description: Chemistry Ranked Entities And Property Curves helps plan analysis reports that need a named ranked list of chemical entities or a property-versus-coordinate curve. Use it when you must print per-entity scores, scan ranges, and the key constants or errors from a sweep.
github: "https://github.com/tangxiangru/AutoR/tree/main/src/skills/chemistry-ranked-entities-and-property-curves"
language: Python
stars: 804
forks: 25
install: "npx degit https://github.com/tangxiangru/AutoR/tree/main/src/skills/chemistry-ranked-entities-and-property-curves ~/.claude/skills/chemistry-ranked-entities-and-property-curves"
installs_to: ~/.claude/skills/chemistry-ranked-entities-and-property-curves
source_path: src/skills/chemistry-ranked-entities-and-property-curves/SKILL.md
collection_size: 25
category_size: 668
collection_url: "https://dirskills.com/collections/tangxiangru/AutoR"
added: 2026-08-22T05:22:29.242Z
last_synced: 2026-08-22T05:22:29.242Z
canonical_url: "https://dirskills.com/skills/chemistry-ranked-entities-and-property-curves"
---

# Chemistry Ranked Entities And Property Curves

Chemistry Ranked Entities And Property Curves helps plan analysis reports that need a named ranked list of chemical entities or a property-versus-coordinate curve. Use it when you must print per-entity scores, scan ranges, and the key constants or errors from a sweep.

**Install:**

```bash
npx degit https://github.com/tangxiangru/AutoR/tree/main/src/skills/chemistry-ranked-entities-and-property-curves ~/.claude/skills/chemistry-ranked-entities-and-property-curves
```

## README

# Print the named-entity ranked list and the property-versus-coordinate curve -- chemistry's two most-computed, least-reported artifacts

Two chemistry deliverables are routinely computed and never printed. Plan both into the report skeleton.

First, the ranked list. Whenever the method scores individual entities -- per-residue scans, per-atom or per-fragment attributions, per-pose scores, per-molecule rankings -- the deliverable is an explicit table of the leading entities by chemical identifier with their scores and units, plus the scan's bookkeeping: how many entities were scanned and the observed minimum and maximum. An aggregate ranking metric (AUC, precision@k, a correlation) does not substitute for the named list. If a per-entity file exists in your outputs, sorting its head into the report is the result. Then map those entities back onto chemistry -- which contacts, which functional groups, which charges or multipoles -- and state whether that is what a chemist would expect.

Second, the curve. Where a property depends on a governing physical or protocol coordinate -- bond length, intermolecular separation, cutoff radius, temperature, training-set size, number of sampling steps -- sweep it and plot the continuous curve with the reference overlaid, then read the derived constants off it and report their errors: equilibrium geometry, well depth, barrier height, asymptotic decay exponent, sum rules and conservation checks. A bar chart of RMSE by model variant answers a different question and does not replace it.

Make both artifacts self-supporting: metric value, N and the comparison annotated inside the panel, and the headline restated in the abstract in the field's units.

## Why this is here

These are the two documented computed-but-never-printed failures. One run's per-entity output file already held the exact ranked list and range the hidden criterion wanted; the report published a pooled AUC and precision@k instead and scored 18 and 0 across two runs -- one sort-and-head away from the answer. Separately, a right result delivered as a bar chart of RMSE by variant instead of the energy-versus-separation curve with the reference overlaid scored 45, 5, 5 across three runs. It also forces the interpretation-onto-named-chemical-entities demand that appears in 4 of 4 tasks.