AC create-fto-screening-report-ip
Create a traceable, screening-level freedom-to-operate report from a supplied risk-point Word document and user-approved PatSnap search expressions. Use when a patent analyst, IP team, product counsel, or R&D owner needs structured feature extraction, PatSnap patent retrieval, claim-data collection, claim-limitation comparison, candidate risk triage, HTML/DOCX reporting, and evidence JSON. Supports a bundled global PatSnap REST workflow or normalized evidence from verified PatSnap MCP connectors. The output is an FTO screening, not a legal clearance opinion.
Create a traceable, screening-level freedom-to-operate report from a supplied risk-point Word document and user-approved PatSnap search expressions.
As a process C 56/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- 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: 12. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "copyright"
Process rating: all ten parameters 56/100
- 0Result and completion. Does not say what the result is
- 30Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 5 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70Execution cost. Instruction body is 4861 tokens
- 100Steps. 214 steps
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 15 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 564: enough signal without eating the budget
- +4Structure: 41 headings
- +3Step-by-step instructions: 214 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.