CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

tooluniverse-binder-discovery

Discover novel small-molecule binders for protein targets using structure-based and ligand-based screening. Covers druggability assessment, known-ligand mining (ChEMBL, BindingDB), similarity expansion, ADMET filtering, and synthesis feasibility. Use for hit identification, virtual screening, target-to-compounds workflows, and lead-finding before commit-to-medchem.

Quality

87%

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

The canonical home for this skill is tooluniverse-binder-discovery in mims-harvard/ToolUniverse

SKILL.md
Quality
Evals
Security

Quality

Content

77%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 dense, highly actionable workflow document whose tool-specific knowledge (exact parameter names, fallback chains, thresholds, validation gates) earns its context cost. Its main structural defect is that every reference file it points to is missing from the bundle, which undermines both progressive disclosure and the report/checklist steps it relies on; minor trimming (known biology, repeated API-key notes) would raise conciseness.

Suggestions

Ship the five referenced files (WORKFLOW_DETAILS.md, TOOLS_REFERENCE.md, REPORT_TEMPLATE.md, EXAMPLES.md, CHECKLIST.md) in the skill bundle, or inline their essential content — currently every reference link dead-ends and steps like 'Initialize with all section headers from the template' cannot be executed.

Compress the Binding Site Reasoning section to the strategy-selection decisions and user warnings (which phase to prioritize, when to check MolGlueDB) and drop the generic medicinal-chemistry facts Claude already knows (e.g., 'Enzymes with active sites... deep, well-defined pockets. Classic small molecule territory').

State the NVIDIA_API_KEY requirement once in the Runtime Notes section and remove the repeated inline '(requires NVIDIA_API_KEY env var; free key at build.nvidia.com)' annotations in Phase 0.

DimensionReasoningScore

Conciseness

The bulk of the body is non-derivable, earned content — exact tool names, parameter quirks ('`smiles` must be a list', 'SMILES must contain `[*{min-max}]`'), fallback chains, and runtimes. Minor padding a pass would trim: the Binding Site Reasoning section explains structural biology Claude already knows ('deep, well-defined pockets. Classic small molecule territory'; 'Nuclear receptors: deep hydrophobic pockets'), the KEY PRINCIPLES list restates later sections, and the '(requires NVIDIA_API_KEY env var; free key at build.nvidia.com)' note repeats five times. This fits anchor 4's 'minor instances of over-explanation' better than anchor 3's 'some unnecessary explanation', but not anchor 5's 'every token earns its place'.

4 / 5

Actionability

Mostly copy-paste-ready guidance: 'ChEMBL_search_targets(pref_name__contains=target_name, organism="Homo sapiens")', 'NvidiaNIM_genmol(smiles="...core...[*{3-8}]...tail...[*{1-3}]...", num_molecules=100, temperature=2.0, scoring="QED")', specific cutoffs (IC50/Ki/Kd < 10 uM, QED > 0.3, MW 200-600), and a fully executable Programmatic Access section. Not a 5: 'NvidiaNIM_boltz2(polymers=[...], ligands=[...])' is an abbreviated sketch, and report initialization defers to 'all section headers from the template (see REPORT_TEMPLATE.md)' — a file absent from the bundle. Well above anchor 3's 'pseudocode instead of executable code'.

4 / 5

Workflow Clarity

Phases 0-7 are explicitly ordered with validation checkpoints throughout: verify tool parameters before calling unfamiliar tools ('Common parameter corrections (verify with `get_tool_info` if uncertain)'), 'Dock a known reference inhibitor first to validate the binding pocket geometry before running candidates', pLDDT gates ('<70 use with caution'), decision points ('If no tractability data... explicitly warn the user before proceeding'), a filter funnel summary, and a pre-delivery CHECKLIST.md invocation, plus fallback chains for every step. This matches anchor 5's 'explicit validation steps; feedback loops for error recovery; checklists for complex processes' rather than anchor 4's 'minor validation gaps' — the batch operations (ADMET filtering, top-20 docking) all carry verification, so the batch-cap at 3 does not apply.

5 / 5

Progressive Disclosure

The body is well-sectioned with clearly signaled one-level-deep pointers ('parameters in TOOLS_REFERENCE.md', 'see REPORT_TEMPLATE.md') and a dedicated Reference Files index describing each file — but scored against the actual bundle, none of the five referenced files (WORKFLOW_DETAILS.md, TOOLS_REFERENCE.md, REPORT_TEMPLATE.md, EXAMPLES.md, CHECKLIST.md) exist; the bundle contains only SKILL.md, so navigation dead-ends and the deferred detail is unavailable. Not anchor 4 ('minor organization gaps') because dangling references are a structural failure, but above anchor 2 since the in-body structure and signaling are good.

3 / 5

Total

16

/

20

Passed

Description

92%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 action coverage, an explicit and well-scoped 'Use for' trigger clause, and a clear boundary against downstream medchem work. The only gap is a few natural synonyms a user might say ('drug discovery', 'find inhibitors'), which keeps trigger-term quality at 4 rather than 5.

DimensionReasoningScore

Specificity

Multiple concrete actions with comprehensive pipeline coverage, all in third person: 'Discover novel small-molecule binders for protein targets using structure-based and ligand-based screening. Covers druggability assessment, known-ligand mining (ChEMBL, BindingDB), similarity expansion, ADMET filtering, and synthesis feasibility.' Anchor 5 fits — the actions span the whole workflow with named data sources — whereas anchor 4 would require 'minor gaps in coverage'.

5 / 5

Completeness

Explicitly answers both questions: the 'what' is 'Discover novel small-molecule binders for protein targets... Covers druggability assessment, known-ligand mining, similarity expansion, ADMET filtering, and synthesis feasibility', and the 'when' is a concrete 'Use for...' clause ('hit identification, virtual screening, target-to-compounds workflows, and lead-finding before commit-to-medchem'). This matches anchor 5 exactly; anchor 4 would need a weaker or less specific 'when'.

5 / 5

Trigger Term Quality

Good natural-term coverage: 'Use for hit identification, virtual screening, target-to-compounds workflows, and lead-finding before commit-to-medchem' plus 'small-molecule binders for protein targets' — phrases domain users actually say. Not 5 because common synonyms are missing ('drug discovery', 'find inhibitors for a target', 'hit finding'), and not 3 because coverage goes well beyond 'some relevant keywords'.

4 / 5

Distinctiveness Conflict Risk

Clear niche — small-molecule binder discovery anchored by named databases (ChEMBL, BindingDB) — with an explicit boundary against the adjacent skill ('before commit-to-medchem'), and trigger terms (hit identification, virtual screening, lead-finding) that do not plausibly fire for sibling skills like data-wrangling or medchem-optimization. Fits anchor 5's 'clear niche with distinct triggers; minimal conflict risk' rather than anchor 4's 'minor overlap risk'.

5 / 5

Total

19

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 5 missing

Warning

Total

15

/

16

Passed

Repository

mims-harvard/ToolUniverse

Path

plugins/tooluniverse/skills/tooluniverse-binder-discovery/SKILL.md

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.