pg-config-tuning

pg-config-tuning is a Backend performance & caching skill for AI agents, published by isdaniel in the pgtuner_mcp repository on GitHub. Skillspace rates pg-config-tuning D (63/100) and it passed the safety scan; the rating is based on static analysis only.

Guides PostgreSQL configuration tuning based on hardware profile, workload type, and current settings. Covers memory, WAL, checkpoints, autovacuum, planner, and connection settings with specific ALTER SYSTEM recommendations. Teaches the agent to use review_settings with individual categories and understand restart vs reload requirements.

Grade
D
Quality
63 / 100
Safety
Passed
GitHub stars
25

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubisdaniel/pgtuner_mcp

Our review

Architecture
90 / 100
Maturity
Basic: a single SKILL.md
Security scan
No issues found
License
Apache-2.0
Adoption
Adopted by 0 other repositories, in 0 collections

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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