by sidequery · MCP Server · ★ 140
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
uv add sidemantic
uv add "sidemantic[malloy]"Taken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 140 |
| Forks | 14 |
| Language | Python |
| Category | MCP Server |
| License | AGPL-3.0 |
| Quality Score | 63/100 |
| Open Issues | 1 |
| Last Updated | 2026-11-06 |
| Created | 2025-10-04 |
| Platforms | mcp, python |
| Est. Tokens | ~16k |
Sidemantic The universal metrics layer for consistent metrics across your data stack. Compatible with 15+ semantic model formats. Supported Formats: Sidemantic (YAML, Python or SQL), Power BI TMDL, Cube, dbt MetricFlow, LookML, Hex, Rill, Superset, Omni, BSL, GoodData LDM, Snowflake Cortex, Malloy, OSI, AtScale SML, ThoughtSpot TML Databases: DuckDB, MotherDuck, PostgreSQL, BigQuery, Snowflake,...
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: