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forgemeshlabs/aso-audit-mcp (@forgemeshlabs/aso-audit-mcp)

forgemeshlabs-aso-audit-mcp · v0.1.4 · scanned

What changed in the harness

Selection accuracy 98%, 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.

01Safety

30.0 / 30

30.0 out of 30
02Legibility

29.4 / 30

29.4 out of 30
03Economics

20.0 / 20

20.0 out of 20
04Discoverability

12.6 / 20

12.6 out of 20

Highest-impact fix

Estimated gain +7 points

Make 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
get_fix_plan get_aso_framework low Both relate to ASO scoring, but get_fix_plan requires a url and scans a site while get_aso_framework takes no input and returns static reference docs; a task asking about 'ASO scoring/points' could momentarily blur which to call, though descriptions clearly diverge (actionable scan vs framework reference).
check_signal list_checks low A task like 'check for llms.txt signal' could tempt calling list_checks instead of check_signal if the agent is unsure of valid check_id values, but list_checks is clearly a catalog lookup with no scanning capability, so confusion is unlikely once schemas are read.

Compare the field

One score is useful.
The evidence makes it actionable.

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