Trueline Mcp
Repository: trueline-mcp
Author: rjkaes · Source status: Clear source
Score 82Clear source
Manual reviewSmarter reads, safer edits.
Score basis：Clear source · Risk needs review · Universal
Author unclaimed
Universal
12
Compare skills
Pick 2–4 skills and compare what really matters: fit, risk, install effort, and community signal.
Selected skills (2/4)
Comparison matrix
Highlights show current best; tooltip explains diff/best rules.
SAS-v2.1 diff rules / risk tag notes
Start with the matrix. Open this section when you need to understand audit grades, top threats, control gaps, and best-value highlights.
Suggested baseline
Search to add skills, or paste 2–4 comma-separated slugs.
How differences are detected
A row is marked different when selected skills have distinct values. Only-differences mode hides rows that are identical.
How best values are highlighted
Audit score, evidence confidence, trust score, and community signal prefer higher values; execution risk and install friction prefer lower values.
How to read risk tags
Risk tags come from SAS-v2.1 public-evidence signals and point to command, network, secret, context, or supply-chain items to review before install.
Selected audit signals
learn-low-code-agentic-ai
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
agentic-ai-engineering
Execution risk：High
Threat tags：prompt injection, tool poisoning, unexpected code execution
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | learn-low-code-agentic-ai | agentic-ai-engineering |
|---|---|---|
| SAS-v2.1 pre-install audit | ||
Threat tags | unexpected code execution, data exfiltration, human approval gap | prompt injection, tool poisoning, unexpected code execution |
Evidence confidence | 65% | 68% |
| Source & provenance | ||
Provenance | panaversity/learn-low-code-agentic-ai | agenticloops-ai/agentic-ai-engineering |
Freshness | 2025-10-08 | 2026-04-07 |
| Risk & trust | ||
Trust score | 67 | 82 |
Audit signals | network access | No explicit signals |
| Community | ||
Stars | 443 | 49 |
Repository: splitrail
Author: Piebald-AI · Source status: Clear source
Fast, cross-platform, real-time token usage tracker and cost monitor for Gemini CLI / Claude Code / Codex CLI / Qwen Code / Cline / Roo Code / Kilo Code / GitHub Copilot / OpenCode / Pi Agent / Piebald.
Score basis：Clear source · Risk needs review · Universal
Repository: claude-pace-maker
Author: LightspeedDMS · Source status: Clear source
Prevent Claude Code overages by throttling tool usage when getting close to the 5-hour limit and weekly limit.
Score basis：Clear source · Risk needs review · Universal
Repository: learn-agentic-ai
Author: panaversity · Source status: Clear source
Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes.
Score basis：Clear source · Risk needs review · Universal
Repository: learn-agentic-ai-from-low-code-to-code
Author: panaversity · Source status: Clear source
Build production-grade agents with OpenAI AgentKit, a no-code platfrom.
Score basis：Clear source · Risk needs review · Universal