AF drugflow-skills
Multi-flow API workflow skill for this DrugFlow Django repository. Use when an agent needs executable end-to-end API procedures such as login/register, workspace and balance retrieval, job listing, virtual screening, docking, ADMET, rescoring, structure extraction, and molecular factory.
As a process F 36/100 · Will not run — References files that are not bundled: scripts/<flow>/, references/flows/<flow>/
How to improve
- The text references files that are not there: add them or drop the references.
- 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: 28. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: scripts/<flow>/ - warning
missing-refreference to a missing file: references/flows/<flow>/
Process rating: all ten parameters 36/100
- 0Tools and files. 2 referenced file(s) missing: scripts/<flow>/, references/flows/<flow>/
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 7 mutating operations with no state check
- 40Consistency. Frontmatter name (drugflow-skills) differs from the folder (drugflow-api)
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 89 steps
- 100Execution cost. Instruction body is 1677 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 12 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (3 tags): a typed call is more reliable
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)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 288: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 89 items
- +3Output format is stated explicitly
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.