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Public assessment

VoxellInc/forge-mcp (@voxell/forge-mcp)

voxell-forge-mcp · v0.1.5 · scanned

What changed in the harness

Selection accuracy 95→95, token cost up 2%, unconfirmed writes 0%→0%.

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.

01Safety

0.0 / 30

0.0 out of 30
02Legibility

28.8 / 30

28.8 out of 30
03Economics

20.0 / 20

20.0 out of 20
04Discoverability

8.8 / 20

8.8 out of 20

Highest-impact fix

Estimated gain +30 points

Add explicit identity and permission preflight tools

Expose machine-readable principal/tenant confirmation and a non-mutating permission check so agents can verify both before destructive actions.

Description evidence

Defects and rewrites.

1 defect 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
list_models
name_restates_behavior
Returns the set of embedding models Forge supports, each with its id, native vector dimensionality, and whether it is the default — use this to pick a model id to pass to the embed tool before generating embeddings.

Selection evidence

Confusable tool pairs.

0 pairs where similar names or overlapping descriptions may send an agent toward the wrong tool.

Tool A Tool B Confidence Why they collide
No confusable tool pairs were flagged in this assessment.

Compare the field

One score is useful.
The evidence makes it actionable.

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