BD biologist-analyst
Analyzes living systems and biological phenomena through biological lens using evolution, molecular biology, ecology, and systems biology frameworks. Provides insights on mechanisms, adaptations, interactions, and life processes. Use when: Biological systems, health issues, evolutionary questions, ecological problems, biotechnology. Evaluates: Function, structure, heredity, evolution, interactions, molecular mechanisms.
Analyzes living systems and biological phenomena through biological lens using evolution, molecular biology, ecology, and systems biology frameworks.
As a process D 47/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
The same skill appears in 1 more place: RA-Skills
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 8242 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 47/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 8 mutating operations with no state check
- 40Execution cost. Instruction body is 8242 tokens: crowds the task out of the window
- 100Tools and files. No external tools needed
- 100Steps. 360 steps
- 100Consistency. Name and required fields are in place
- low 12 top-level sections: this looks like several domains in one skill
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 423: enough signal without eating the budget
- +4Structure: 50 headings
- +3Step-by-step instructions: 360 items
- +4Has examples (0 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.