SKILLEMALL.ai
GitHub ↗ RU Sign in

AB sar-analysis

Structure-activity relationship analysis workflows using SciMiner's MCS-based and scaffold-based SAR APIs for file or inline table inputs, plus an AlphaFold3-based binding-mode prediction workflow for target-aware SAR.

ClawHub Agent Skills author: SciMiner v1.0.0 MIT-0 4 files body ≈ 2 541 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Structure-activity relationship analysis workflows using SciMiner's MCS-based and scaffold-based SAR APIs for file or inline table inputs, plus an…

As a process B 66/100 · Nearly there — weak spots: result and completion, when it triggers, running it twice

ProcedureData 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%
100
Quality 40%
83
Run on models
none yet
Process rating
B
66/100
Nearly there
Result and completion w 14
0
When it triggers w 12
20
Running it twice w 4
30
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 · 0

    ✓ No critical or high findings

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "credential_files"

    Process rating: all ten parameters 66/100

    • 0Result and completion. Does not say what the result is
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 5 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 64 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2541 tokens
    • 100Progress reporting. Reports progress

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 218: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 64 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

    External checks

    ClawHub: suspicious
    This SAR skill has a legitimate scientific workflow, but it gives the agent unusually broad network and file-write capability around a local SciMiner API key.
    LLM: suspicious (high) · VirusTotal: · 9 Jul 2026