BB assess-technology-market-and-patent-landscape-ip
Assess a defined product or technology field for project initiation by combining current market evidence, a reproducible global patent landscape, individually validated key players, technical themes and gap hypotheses, jurisdictional filing footprint, competitive tiers, risks, and differentiated project options in a self-contained scientific HTML report. Use for technology-market landscape, patent landscape, opportunity mapping, or R&D project-entry decisions.
Assess a defined product or technology field for project initiation by combining current market evidence, a reproducible global patent landscape, individually…
As a process B 71/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting
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 ≈ 5453 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "copyright"
Process rating: all ten parameters 71/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 9 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 5453 tokens
- 100Tools and files. No external tools needed
- 100Steps. 227 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- low 13 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 464: enough signal without eating the budget
- +4Structure: 61 headings
- +3Step-by-step instructions: 227 items
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.