A
licenseNot graded
qualityB
maintenanceEnables AI agents to search, read, and traverse a local knowledge base of Markdown files using full-text search and relationship graph, reducing token usage.
MIT
search-docs
by otolab
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TDQS
A3.7/5.0
Scored across 10 tools
Disambiguation5/5
Each tool has a clearly distinct purpose: status checks, search, outline, index maintenance, related project management, initialization, and document retrieval. No two tools overlap in function or ambiguity.
Naming Consistency2/5
Naming conventions are inconsistent. While get_* tools are consistent, index_status, index_purge, maintenance_repair, and init deviate from a uniform verb_noun pattern, mixing noun-first and bare verb forms.
Tool Count5/5
10 tools is well within the ideal range for a search-docs server. Each tool covers a distinct aspect of the domain (search, indexing, project management, init) without redundancy.
Completeness3/5
The surface covers core operations but has gaps: no remove_related_project to complement add_related_project, and no explicit index rebuild tool (only mentioned as a post-repair step). Additionally, there is no direct way to list all documents beyond index status counts.
Maintenance
ActivityMaintained
ResponsivenessResponsive