Compare skills
Pick 2–4 skills and compare what really matters: fit, risk, install effort, and community signal.
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
Repository: langfuse-python
Author: langfuse · Source status: Clear source
🪢 Langfuse Python SDK - Instrument your LLM app with decorators or low-level SDK and get detailed tracing/observability.
Score basis：Clear source · Risk needs review · Universal
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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
langfuse
Execution risk：High
Threat tags：prompt injection, tool poisoning, unexpected code execution
Control gaps：missing license, broad permissions, shell without guardrails
httptap
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
centreon
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | langfuse | httptap | centreon |
|---|---|---|---|
| SAS-v2.1 pre-install audit | |||
Audit grade | C · Review first | C · Review first | C · Review first |
Execution risk | High | High | High |
Threat tags | prompt injection, tool poisoning, unexpected code execution | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, data exfiltration, human approval gap |
Control gaps | missing license, broad permissions, shell without guardrails | missing license, broad permissions, shell without guardrails | missing license, broad permissions, shell without guardrails |
Permission summary | Permission review, Network, Command | Permission review, Network, Command | Permission review, Network, Command |
Evidence confidence | 67% | 65% | 65% |
| Source & provenance | |||
Provenance | langfuse/langfuse | ozeranskii/httptap | centreon/centreon |
Category | Operations & Infra | Operations & Infra | Operations & Infra |
Freshness | |||
| Risk & trust | |||
Trust score | 79 | 79 | 79 |
Audit signals | |||
| Install & compatibility | |||
Supported tools | Universal | Universal | Universal |
Install method | script-backed | script-backed | script-backed |
Install friction | |||
| Community | |||
Stars | 24.4K | 486 | 148 |
Repository: langfuse-js
Author: langfuse · Source status: Clear source
🪢 Langfuse JS/TS SDKs - Instrument your LLM app and get detailed tracing/observability.
Score basis：Clear source · Risk needs review · Universal
Repository: oss-llmops-stack
Author: langfuse · Source status: Clear source
Modular, open source LLMOps stack that separates concerns: LiteLLM unifies LLM APIs, manages routing and cost controls, and ensures high-availability, while Langfuse focuses on detailed observability, prompt versioning,…
Score basis：Clear source · Risk needs review · Universal
Repository: Stream-Daemon
Author: ChiefGyk3D · Source status: Clear source
Stream Daemon is an open-source automation tool for live streamers and creators.
Score basis：Clear source · Low risk signals · Universal
2026-04-06 |
2026-04-06 |
2026-04-06 |
No explicit signals |
network access |
network access |
Permission hints | repository clone, local runtime dependencies | repository clone, local runtime dependencies | repository clone, local runtime dependencies |
|---|
40 |
40 |
40 |
