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universal-memory

universal-memory

by YanAmorelli
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Python
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Deploy Server
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TDQS

A4.1/5.0

Scored across 38 tools

Disambiguation3/5

Many skill tools overlap in purpose (create_skill, create_skill_draft, publish_skill, import_skill, adopt_skill, generate_skill, promote_skill_recommendation), and latent-skill tools require careful reading. The descriptions explicitly cross-reference alternatives, so an agent can usually pick correctly, but the boundaries remain subtle.

Naming Consistency4/5

Overwhelmingly snake_case with predictable verb_noun forms for most operations. A few noun-only or status-style tools (status, context, bootstrap, doctor, host_setup, host_check) break the strict verb_noun pattern but remain readable and consistent in casing.

Tool Count2/5

38 tools is well above the 25-tool threshold, and the server spans several subdomains: memory facts, skill lifecycle, project setup, host configuration, audit, and snapshots. Many skill tools are highly specialized, but the total surface is heavy for an agent to navigate.

Completeness4/5

Skill lifecycle coverage is exceptionally complete: draft, validate, publish, update, rename, sync, import, adopt, latent proposal, promotion, cleanup, activate/deactivate. Memory facts have create/list/purge and compiled context, but there is no direct update_fact, forcing purge-and-recreate for edits.

Maintenance

ActivityMaintained
ResponsivenessNo recent community issues

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