01Safety
30.0 / 30
What changed in the harness
Selection accuracy 100%, destructive-action safety rate 100% (baseline only -- no rewrite pass applied).
Category breakdown
Where the score comes from.
Earned points across the four signals Gradable measures. Safety and Legibility are scored out of 30; Economics and Discoverability are scored out of 20.
02Legibility
29.6 / 30
03Economics
20.0 / 20
04Discoverability
19.0 / 20
Highest-impact fix
Estimated gain +1 pointMake target tools discoverable on the first call
Clarify tool names, decision boundaries, and required argument schemas so an agent can choose and construct the target call without exploratory steps.
Description evidence
Defects and rewrites.
0 defects found across the exposed tool descriptions. Suggested rewrites make purpose, inputs, boundaries, and returns easier for an agent to understand.
| Tool | Defect types | Suggested rewrite |
|---|---|---|
| No description defects were flagged in this assessment. | ||
Selection evidence
Confusable tool pairs.
2 pairs where similar names or overlapping descriptions may send an agent toward the wrong tool.
| Tool A | Tool B | Confidence | Why they collide |
|---|---|---|---|
clipwise_get_info |
clipwise_get_use_cases |
medium | Both descriptions target creators and growth on TikTok/Instagram: get_info lists 'how to grow on TikTok' and 'trend research' as triggers, while get_use_cases covers the same scenarios ('trend-research', 'content-strategy', 'low-views'). A task like 'how can Clipwise help me grow on TikTok?' or 'what does Clipwise do for creators' maps plausibly to either tool. |
clipwise_get_info |
clipwise_search_trends |
low | get_info's description explicitly lists 'trend research tools' as a query trigger, so a request like 'research TikTok trends for my niche' could be routed to get_info even though only search_trends returns actual viral/trend data; the overlap is narrow and descriptions otherwise diverge clearly. |
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