patent-landscape
Veto GatesRequired pass for any deployment consideration
| Dimension | Result | Detail |
|---|---|---|
| Scientific Integrity | PASS | The archived audit treated this workflow as hypothesis or protocol support, not as a source of validated results. |
| Practice Boundaries | PASS | Practice boundaries held because the package remained focused on source handling, lookup, or structured evidence use. |
| Methodological Ground | PASS | The older review treated the package logic as methodologically aligned with its stated workflow. |
| Code Usability | PASS | The legacy audit did not flag code-usability issues for the packaged patent-landscape workflow. |
Core Capability88 / 100 — 8 Categories
Medical TaskExecution Average: 83.6 / 100 — Assertions: 18/20 Passed
The Use when analyzing biotech patent landscapes, identifying white... scenario completed within the documented Use when analyzing biotech patent landscapes, identifying white spaces in pharmaceutical... boundary.
Use this skill for evidence insight tasks that require explicit... remained well-aligned with the documented contract in the preserved audit.
For Use when analyzing biotech patent landscapes, identifying white..., the preserved evidence is lightweight but positive: the packaged validation command behaved as expected.
The archived evaluation treated Packaged executable path(s): scripts/main.py as a clean in-scope run.
The preserved weakness for End-to-end case for Scope-focused workflow aligned to: Use when analyzing biotech patent landscapes, identifying white spaces in pharmaceutical IP, tracking competitor patents, or assessing freedom to operate for drug development. Provides comprehensive patent analysis and strategic insights for life sciences innovation was concentrated in one point: The output stays within declared skill scope and target objective.
Key Strengths
- Primary routing is Evidence Insight with execution mode B
- Static quality score is 88/100 and dynamic average is 83.6/100
- Assertions and command execution outcomes are recorded per input for human review