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Phoenix Arize Setup Skill — measured AI agent skill | DecimalAI

a5c-ai/phoenix-arize-setup

SkillScore23Maintained

Arize Phoenix observability platform setup for LLM debugging and evaluation

by a5c-ai

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

AI Engineer pack

decimalai skills pull a5c-ai-phoenix-arize-setup

Get this skill — curl · raw file

curl -fsSL https://app.decimal.ai/s/a5c-ai-phoenix-arize-setup/SKILL.md

Raw file: /s/a5c-ai-phoenix-arize-setup/SKILL.md ↗ · machine-readable summary at /s/a5c-ai-phoenix-arize-setup.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

22 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 9d ago

Yes — +23% lift-15% tokens0% turns23% of whole cases pass with skill (5/22)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-04	✗→✓	▲ Improved	-35%	0%
case-15	✗→✓	▲ Improved	1%	0%
case-16	✗→✓	▲ Improved	-11%	0%
case-17	✗→✓	▲ Improved	-2%	0%
case-19	✗→✓	▲ Improved	-39%	0%

Showing 5 of 22 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 7/31/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

a5c-ai / babysitter

library/specializations/ai-agents-conversational/skills/phoenix-arize-setup/SKILL.md

View on GitHub ↗

License MITImported 7/31/2026Version v1

Skill contents

SKILL.md

Phoenix Arize Setup Skill

Capabilities

Set up Phoenix local server
Configure tracing instrumentation
Design evaluation experiments
Implement embedding visualizations
Set up retrieval analysis
Create custom evaluations with LLM-as-judge

Target Processes

llm-observability-monitoring
agent-evaluation-framework

Implementation Details

Core Features

Tracing: OpenTelemetry-based LLM traces
Evals: LLM-as-judge evaluations
Embeddings: Visualization and drift detection
Retrieval: RAG quality analysis
Datasets: Experiment management

Instrumentation

OpenAI auto-instrumentation
LangChain instrumentation
LlamaIndex instrumentation
Custom span creation

Configuration Options

Phoenix server setup
Trace sampling
Evaluation metrics
Embedding models
Export settings

Best Practices

Comprehensive instrumentation
Regular evaluation runs
Monitor embedding drift
Analyze retrieval quality

Dependencies

arize-phoenix
openinference-instrumentation-openai

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Other measured skills in the registry, with their headline benchmark lift.