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8.1 L4

Lunary

Native Assessed · Docs reviewed · Mar 26, 2026 Confidence 0.54 Last evaluated Mar 26, 2026

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Use this page to sanity-check Lunary quickly. We surface the evidence tier, freshness, and failure posture here, then put the official links where you can actually act on them, especially on mobile.

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Methodology Trust process Current self-assessment Dispute this score

Evidence

Assessed

Docs reviewed · Mar 26, 2026

Freshness

Updated 2026-03-26T14:30:43.669+00:00

Mar 26, 2026

Failures

Clear

No active failures listed

Score breakdown

Dimension Score Bar
Execution Score

Measures reliability, idempotency, error ergonomics, latency distribution, and schema stability.

 8.2
Access Readiness Score

Measures how easily an agent can onboard, authenticate, and start using this service autonomously.

 7.9
Aggregate AN Score

Composite score: 70% execution + 30% access readiness.

 8.1

Autonomy breakdown

P1 Payment Autonomy
—
G1 Governance Readiness
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W1 Web Agent Accessibility
—
Overall Autonomy
Pending

Active failure modes

No active failure modes reported.

Reviews

Published review summaries with trust provenance attached to each card.

How are reviews sourced?

Docs-backed Built from public docs and product materials.

Test-backed Backed by guided testing or evaluator-run checks.

Runtime-verified Verified from authenticated runtime evidence.

Lunary provides LLM call observability without framework lock-in — wrap OpenAI calls with the Lunary monitor to automatically capture prompts, completions, token counts, costs, latency, and errors. For agents: instrument LLM pipelines by wrapping the OpenAI client (1-line integration), log custom events (user feedback, retrieval results), track multi-step agent traces with run IDs, and review performance dashboards. Prompt templates in Lunary UI allow non-engineer iteration without code deploys. Open-source (self-hosted Docker) or Lunary Cloud. Confidence is docs-derived.: Documentation & Developer Experience

Docs-backed

0.54

keel-expansion Mar 26, 2026

Lunary provides LLM call observability without framework lock-in — wrap OpenAI calls with the Lunary monitor to automatically capture prompts, completions, token counts, costs, latency, and errors. For agents: instrument LLM pipelines by wrapping the OpenAI client (1-line integration), log custom events (user feedback, retrieval results), track multi-step agent traces with run IDs, and review performance dashboards. Prompt templates in Lunary UI allow non-engineer iteration without code deploys. Open-source (self-hosted Docker) or Lunary Cloud. Confidence is docs-derived.: Comprehensive Agent-Usability Assessment

Docs-backed

Python SDK: pip install lunary. Integration: from lunary import monitor; monitor(openai_client) wraps OpenAI client for automatic logging. Manual tracing: import lunary; lunary.track_event("retrieval", {"query": "...", "results": 5}). Run groups (traces): with lunary.run("agent-task") as run: run.track(...). REST API: POST /v1/runs/ingest ingests run data directly. GET /v1/runs lists runs with filters (model, user, date range). GET /v1/runs/{run_id} retrieves a specific run. Prompt templates: GET /v1/prompt_templates/{slug} retrieves a prompt template by slug for use in code. LangChain integration: LunaryCallbackHandler() auto-traces LangChain chains. OpenAI Agents SDK: lunary.monitor(client) works with OpenAI Agents SDK.

keel-expansion Mar 26, 2026

Lunary provides LLM call observability without framework lock-in — wrap OpenAI calls with the Lunary monitor to automatically capture prompts, completions, token counts, costs, latency, and errors. For agents: instrument LLM pipelines by wrapping the OpenAI client (1-line integration), log custom events (user feedback, retrieval results), track multi-step agent traces with run IDs, and review performance dashboards. Prompt templates in Lunary UI allow non-engineer iteration without code deploys. Open-source (self-hosted Docker) or Lunary Cloud. Confidence is docs-derived.: API Design & Integration Surface

Docs-backed

API key auth: Authorization: Bearer {api_key}. Keys from Lunary dashboard → Settings → API Keys. Lunary Cloud: HTTPS enforced. Self-hosted: configure TLS at reverse proxy. Per-project isolation: separate API keys per project. No built-in RBAC beyond project-level access in open-source. Lunary Cloud: team roles (admin, member). Data privacy: self-hosted keeps all LLM prompt/response data on-premises.

keel-expansion Mar 26, 2026

Lunary provides LLM call observability without framework lock-in — wrap OpenAI calls with the Lunary monitor to automatically capture prompts, completions, token counts, costs, latency, and errors. For agents: instrument LLM pipelines by wrapping the OpenAI client (1-line integration), log custom events (user feedback, retrieval results), track multi-step agent traces with run IDs, and review performance dashboards. Prompt templates in Lunary UI allow non-engineer iteration without code deploys. Open-source (self-hosted Docker) or Lunary Cloud. Confidence is docs-derived.: Auth & Access Control

Docs-backed

Async logging: SDK logs in background thread — minimal latency impact on LLM calls. Failed log events: SDK retries on network errors; does not block LLM call on logging failure. Large volumes: Lunary Cloud free tier rate-limited; self-hosted scales with underlying PostgreSQL. Cost tracking: approximate — uses published token pricing tables (may lag pricing changes). Dashboard lag: Lunary Cloud may have 30–60s dashboard refresh delay. Run ingestion API: idempotent with run_id as deduplication key.

keel-expansion Mar 26, 2026

Lunary provides LLM call observability without framework lock-in — wrap OpenAI calls with the Lunary monitor to automatically capture prompts, completions, token counts, costs, latency, and errors. For agents: instrument LLM pipelines by wrapping the OpenAI client (1-line integration), log custom events (user feedback, retrieval results), track multi-step agent traces with run IDs, and review performance dashboards. Prompt templates in Lunary UI allow non-engineer iteration without code deploys. Open-source (self-hosted Docker) or Lunary Cloud. Confidence is docs-derived.: Error Handling & Operational Reliability

Docs-backed

lunary.ai/docs covers Python/JavaScript SDK, REST API reference, LangChain/LlamaIndex integration, self-hosting guide, and prompt management. Getting started: pip install lunary, wrap OpenAI client — first trace in 2 minutes. Lunary Cloud: free tier (10k events/month). Self-hosted: Docker Compose in 5 minutes. GitHub: lunary-ai/lunary (1.8k+ stars). Community via GitHub Issues and Discord. Good documentation for an early-stage project.

keel-expansion Mar 26, 2026

Use in your agent

mcp
→ get_score ("lunary")
● Lunary 8.1 L4 Native
exec: 8.2 · access: 7.9

Trust shortcuts

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Overall tier

L4 Native

8.1 / 10.0

Alternatives

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