SKILLEMALL.ai
GitHub ↗ RU Sign in

AC deeppurpose

Help install, inspect, run, troubleshoot, and adapt the DeepPurpose molecular modeling library for drug-target interaction prediction, compound property prediction, DDI, PPI, protein function prediction, drug repurposing, and virtual screening. Use when the user mentions DeepPurpose, `from DeepPurpose import`, `DTI`, `CompoundPred`, `DDI`, `PPI`, `ProteinPred`, `oneliner`, `data_process`, `generate_config`, DeepPurpose datasets, encodings, pretrained models, toy data, or demo notebooks.

ClawHub Agent Skills author: zoeprior v1.0.1 MIT-0 6 files body ≈ 732 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

GeneratorInfrastructureData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
98
Quality 40%
85
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-high-entropy-token references/data-and-pretrained.md:18
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - `load…ase()`
      quoted
    • low Secrets in code secret-high-entropy-token references/data-and-pretrained.md:20
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - `load…ase()`
      quoted

    Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 52/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 39 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 732 tokens
    • 100Running it twice. No mutating operations

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +2Single-language instructions
    • +3Description length 491: enough signal without eating the budget
    • +4Structure: 4 headings
    • +3Step-by-step instructions: 39 items
    • +4Reference files are cited in the instructions (3 of 3)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: clean
    This is a documentation-only helper for using DeepPurpose, with disclosed install and download guidance that fits its stated purpose.
    LLM: benign (high) · VirusTotal: · 29 May 2026