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census-mcp-server: tool descriptions scored

tools/list taken
(UTC)
Scoring rules
v2

Scores, issues and names only

This page shows how census-mcp-server's tool descriptions scored, the issues found and the names of its tools and parameters. The descriptions are the server's own: read them where the copy came from.

This copy comes from Smithery's registry, which keeps each tool's name, description and input schema, but no output schema, annotations or instructions. Points for return values and for marking destructive tools can come out lower than the server's own tools/list would give.

A server with a public URL can be scored as it is today: score from a URL

servers/cyanheads-census-mcp-server
Average score
60.4 / 100Cloudy
Tools
7
Near-identical descriptions
0

Across the server

No server-wide issues.

Tools

census_list_datasets

48 / 100Cloudy

Purpose
20 / 20
When to use
5 / 20
Arguments
15 / 25
Return value
8 / 15
Constraints and side effects
0 / 10
Examples
0 / 10
  • Minor
    No `required` list, so every argument is optional.no_required
  • Minor
    No constraints, side effects, auth or rate limits described, and no annotations.no_constraints

census_list_geographies

53 / 100Cloudy

Purpose
20 / 20
When to use
5 / 20
Arguments
15 / 25
Return value
8 / 15
Constraints and side effects
0 / 10
Examples
5 / 10
  • Minor
    No `required` list, so every argument is optional.no_required
  • Minor
    No constraints, side effects, auth or rate limits described, and no annotations.no_constraints

census_compare_geographies

59 / 100Cloudy

Purpose
20 / 20
When to use
5 / 20
Arguments
16 / 25
Return value
8 / 15
Constraints and side effects
0 / 10
Examples
10 / 10
  • Minor
    No `required` list, so every argument is optional.no_required
  • Minor
    No constraints, side effects, auth or rate limits described, and no annotations.no_constraints

census_get_variable

60 / 100Cloudy

Purpose
20 / 20
When to use
5 / 20
Arguments
15 / 25
Return value
15 / 15
Constraints and side effects
0 / 10
Examples
5 / 10
  • Minor
    No `required` list, so every argument is optional.no_required
  • Minor
    The description mentions none of its 3 or more arguments.params_not_in_description
  • Minor
    No constraints, side effects, auth or rate limits described, and no annotations.no_constraints

census_query_data

65 / 100Cloudy

Purpose
20 / 20
When to use
10 / 20
Arguments
15 / 25
Return value
15 / 15
Constraints and side effects
0 / 10
Examples
5 / 10
  • Minor
    No `required` list, so every argument is optional.no_required
  • Minor
    No constraints, side effects, auth or rate limits described, and no annotations.no_constraints

census_resolve_geography

65 / 100Cloudy

Purpose
20 / 20
When to use
10 / 20
Arguments
17 / 25
Return value
8 / 15
Constraints and side effects
0 / 10
Examples
10 / 10
  • Minor
    No `required` list, so every argument is optional.no_required
  • Minor
    No constraints, side effects, auth or rate limits described, and no annotations.no_constraints

census_search_variables

73 / 100Clear

Purpose
20 / 20
When to use
10 / 20
Arguments
15 / 25
Return value
15 / 15
Constraints and side effects
3 / 10
Examples
10 / 10
  • Minor
    No `required` list, so every argument is optional.no_required

What static scoring cannot tell

This score reads only the text of each description and schema: it says what is written, not what a model will do. Short tools whose names already say what they do, such as browser_close, score low here even when models use them well, and in our measurements current models chose the right tool in one step even from one-line descriptions, as long as the names and schemas differed. What the text cannot show, such as what happens over several steps and whether an added sentence helps or misleads, is what an evaluation measures, on the Pro and Team plans.

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