BB develop-patent-design-arounds-ip
Develop and screen single-patent design-around concepts using an application-requirements baseline, claim-feature and functional reconstruction, TRIZ trimming, evidence-backed function-oriented search, differentiated concept engineering, and jurisdiction-specific claim risk review. Use when a user asks for patent design-around options, non-equivalent alternatives, or a preliminary infringement-risk comparison against a specific patent.
Develop and screen single-patent design-around concepts using an application-requirements baseline, claim-feature and functional reconstruction, TRIZ…
As a process B 68/100 · Nearly there — weak spots: result and completion, execution cost, running it twice
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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 8289 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "copyright"
Process rating: all ten parameters 68/100
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 17 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 40Execution cost. Instruction body is 8289 tokens: crowds the task out of the window
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 351 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- low 19 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 439: enough signal without eating the budget
- +4Structure: 86 headings
- +3Step-by-step instructions: 351 items
- +4Has examples (18 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.