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molecular-docking

End-to-end molecular docking pipeline. Target preparation, pocket detection, protein-ligand docking (DiffDock/Vina), scoring, interaction analysis, and pose ranking.

61

Quality

77%

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tessl review fix ./backend/cli/skills/chemistry/molecular-docking/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

76%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A highly actionable, well-structured pipeline skill with copy-paste-ready commands for every stage and a clean, verified one-level-deep bundle. Its main weaknesses are minor redundancy in the Installation section and the absence of validation checkpoints in the batch virtual-screening workflow.

Suggestions

Add validation checkpoints to the workflows — e.g. after `prepare_target.py`, verify the pocket JSON is non-empty before docking; after `dock.py`, confirm poses.sdf contains poses before scoring — especially in the batch virtual-screening workflow.

Remove the duplicated `pip install biopython` and `pip install rdkit-pypi` lines under "Target preparation"/"Ligand preparation" since they are already in the Core install line.

Move the detailed interaction criteria (bond distances, angles, pi-stacking thresholds) from "Output Interpretation" into `references/` alongside `pocket_detection.md`, keeping only interpretation heuristics inline.

DimensionReasoningScore

Conciseness

The body assumes domain competence and avoids explaining known concepts, but the Overview restates the pipeline stages already in the description, and the install block repeats `pip install biopython` and `pip install rdkit-pypi` under "Target preparation"/"Ligand preparation" after listing them in Core. These minor trimmable instances match anchor 4 rather than the every-token-earns-its-place anchor 5.

4 / 5

Actionability

Four complete workflows give fully executable copy-paste bash invocations with all flags for each of the five scripts, plus a runnable dependency-verification block and an input/output script reference table. This matches anchor 5 ("Fully executable; copy-paste ready code or commands; specific examples cover the common cases") with no notable gaps.

5 / 5

Workflow Clarity

Steps are clearly sequenced across all four workflows, but Workflow 2 (virtual screening) is a batch operation with no validation checkpoint between stages — nothing verifies the prepared target or the docked poses before ranking. The rubric guideline explicitly caps batch operations lacking validation at 3; the Troubleshooting section offers error-recovery hints but not in-workflow feedback loops, so 4 is not reachable.

3 / 5

Progressive Disclosure

Scored against the actual bundle: `references/pocket_detection.md` exists, is clearly signaled with a purpose statement, and is one level deep with no nested references; all five referenced scripts are real files. Good structure with most content appropriately placed matches anchor 4 — not 5 because only pocket detection is offloaded, and inline detail such as the interaction distance/angle thresholds could also live in references.

4 / 5

Total

16

/

20

Passed

Description

71%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A specific, well-scoped description that concretely enumerates the pipeline stages and tools, but it omits any "Use when..." trigger guidance, capping completeness. Adding explicit trigger phrases (including virtual screening, which the body supports) would lift two dimensions.

Suggestions

Append a "Use when" clause with concrete trigger phrases, e.g. "Use when the user asks to dock a ligand, find binding pockets, run virtual screening, or rank docking poses."

Include natural trigger synonyms users actually say — "virtual screening", "active sites", "binding pose" — alongside the existing tool names.

Since a separate diffdock skill exists, phrase the DiffDock mention as pipeline-internal (e.g. "deep-learning docking via an internal DiffDock call") to reduce routing conflicts.

DimensionReasoningScore

Specificity

"Target preparation, pocket detection, protein-ligand docking (DiffDock/Vina), scoring, interaction analysis, and pose ranking" lists multiple concrete named actions with specific tools, comprehensively covering the pipeline stages. This matches the score-5 anchor; there are no meaningful coverage gaps in the action list that would drop it to 4.

5 / 5

Completeness

The "what" is explicit and concrete, but the description contains no "Use when..." clause or equivalent trigger guidance — the rubric guideline caps completeness at 3 in that case. It is not 4 because the "when" is entirely absent rather than merely under-specified.

3 / 5

Trigger Term Quality

Natural terms like "molecular docking", "protein-ligand docking", "pocket detection", "DiffDock", and "Vina" are present, but common user phrases such as "virtual screening", "active site", or "binding pose prediction" are missing. Good keyword coverage with a few natural terms missing matches anchor 4, not the comprehensive synonym coverage of anchor 5.

4 / 5

Distinctiveness Conflict Risk

Molecular docking is a clear niche with distinct triggers, but the description names "DiffDock" while a separate diffdock skill exists, so a "run DiffDock" request could route to either. Mostly distinct with minor overlap risk against a closely related skill matches anchor 4 rather than the minimal-conflict anchor 5.

4 / 5

Total

16

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository

synthetic-sciences/openscience

Path

backend/cli/skills/chemistry/molecular-docking/SKILL.md

Reviewed

Table of Contents

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