CtrlK
BlogDocsLog inGet started
Tessl Logo

ligandmpnn

Inverse-fold a backbone with ligand, nucleic-acid, and metal context using LigandMPNN (Dauparas et al. 2023, github.com/dauparas/LigandMPNN). Reach for this skill to redesign the residues lining a binding pocket around a bound small molecule or cofactor, to design metal-coordinating sites where the geometry must be respected, or to get threaded designed-sequence PDBs out of any MPNN run.

75

Quality

94%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

93%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 lean, dense, highly actionable body: a complete runnable recipe, exact CLI syntax gotchas, a model-selection table, and recognition of silent failure modes with a concrete validation signal. The only improvement space is interleaving validation checkpoints into the run sequence itself rather than isolating them in a troubleshooting section.

DimensionReasoningScore

Conciseness

Every section carries non-obvious, decision-relevant knowledge — the numpy 1.24 sed patch with rationale, exact residue-token grammar ("A45 A46 B10", insertion codes "B82A"), ProDy compiler gotcha, and the silent ligand-drop failure mode. Not 4: no paragraph can be trimmed without losing actionable content; there is no explanation of concepts Claude already knows.

5 / 5

Actionability

Fully executable: copy-paste install line, clone, sed patch, checkpoint fetch, and a complete run.py invocation with real flags; plus an error table mapping exact messages to fixes and a description of the output file layout. Not 4: the common path has no gaps.

5 / 5

Workflow Clarity

The run sequence (install → clone → patch → fetch checkpoints → run → inspect outputs) is unambiguous and there is an explicit validation loop ("If ligand_confidence in the FASTA header is missing or zero across every design, the model never saw the ligand — fix the input, do not trust the sequences"), so the batch-operation cap does not apply. Not 5: the validation checkpoints live in separate troubleshooting sections rather than interleaved into an ordered validate-then-proceed flow.

4 / 5

Progressive Disclosure

No bundle files exist; the ~100-line body is entirely at overview level, cleanly sectioned with meaningful headers, and contains nothing that belongs in a separate file. Cross-links to sibling skills (proteinmpnn, solublempnn, boltz, chai1) are one level deep and clearly signaled. Not 4: navigation is easy and nothing is buried.

5 / 5

Total

19

/

20

Passed

Description

96%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 strong description: concrete third-person actions, explicit 'reach for this skill' triggers covering three distinct scenarios, and natural domain keywords with synonyms. The only soft spot is intentional overlap with the broader MPNN family on the threaded-PDB capability.

DimensionReasoningScore

Specificity

Lists multiple concrete actions in third person — "Inverse-fold a backbone with ligand, nucleic-acid, and metal context", "redesign the residues lining a binding pocket around a bound small molecule or cofactor", "design metal-coordinating sites", "get threaded designed-sequence PDBs" — with comprehensive coverage of the tool's capabilities. Not 4: no meaningful coverage gap; the actions span the full surface of the skill.

5 / 5

Completeness

Explicitly answers both questions: what ("Inverse-fold a backbone with ligand, nucleic-acid, and metal context using LigandMPNN") and when ("Reach for this skill to redesign the residues lining a binding pocket… or to design metal-coordinating sites… or to get threaded designed-sequence PDBs") with three concrete trigger scenarios. Not 4: the when-clause is explicit and specific, not merely present.

5 / 5

Trigger Term Quality

Natural domain phrases a user would actually say are present with synonyms and format terms: "binding pocket", "bound small molecule", "cofactor", "metal-coordinating sites", "backbone", "ligand", "nucleic-acid", "metal", "PDB", "MPNN". Not 4: synonyms (ligand/cofactor/small molecule) and concrete artifacts (PDBs) are covered, not just a few terms.

5 / 5

Distinctiveness Conflict Risk

LigandMPNN names a clear niche with distinct triggers (ligand/NA/metal context), but "get threaded designed-sequence PDBs out of any MPNN run" deliberately claims territory that overlaps sibling proteinmpnn/solublempnn skills. Not 5: that overlap is real even if intentional; not 3: the ligand-context trigger is unmistakable and would not fire for generic skills.

4 / 5

Total

19

/

20

Passed

Validation

81%

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

Validation — 13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

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

Warning

Total

13

/

16

Passed

Repository
aipoch/open-science
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.