add-llm-fallbacks SKILL.md skillA
add-llm-fallbacks from contextjet-ai/awesome-llm-observability is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add contextjet-ai/awesome-llm-observability/add-llm-fallbacks@git:20260705.6b497b1Pins git:20260705.6b497b1 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- contextjet-ai/awesome-llm-observability
- Path
skills/add-llm-fallbacks/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260705.6b497b1, committed Jul 5, 2026
- Size
- 3,375 bytes
- Repository stars
- 45
- License
- a license file GitHub does not identify
Use this to make an LLM app resilient to provider failures, rate limits, timeouts, and outages. Trigger on "handle LLM API errors", "add retries/fallbacks", "the app breaks when OpenAI is down", "rate limit errors", "make my LLM calls reliable", "timeout handling". Add retries, timeouts, and model/provider fallbacks, and observe them so failures are visible.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Add LLM fallbacks and resilience LLM providers rate-limit, time out, 500, and occasionally go down. A single unguarded call means your app goes down with them. Add layered resilience, and instrument it so you can see when it kicks in. ## The layers (add all of them) 1. **Timeouts.** Every call needs a sane timeout. An unbounded call can hang a request forever. Set it based on your p95 latency plus headroom. 2. **Retries with backoff.** Retry transient failures (429, 500, 503, timeouts) with *exponential backoff + jitter*. Cap the number of retries and cap the total wait, and honor `Retry-After` when present. A naive retry loop turns a rate limit into a retry storm (and a big bill, see `reduce-llm-cost`). 3. **Do not retry non-transient errors.** 400s (bad request), auth errors, and content-policy refusals will fail again. Retrying them wastes time and money. 4. **Model / provider fallback.** If the primary model errors or is down, fall back to a secondary (same provider different model, or a different provider). A gateway (LiteLLM, Portkey) gives you this with config instead of code. …
Read the whole file at its exact version.
How to install
mdr add contextjet-ai/awesome-llm-observability/add-llm-fallbacks@sha256:9a65d224bf44d26cThe line at the top of this page pins the label git:20260705.6b497b1, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_b4ywyffzjjzwkrys)
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Versions
The registry has recorded 1 version of this file, committed on Jul 5, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (3375 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
contextjet-ai/awesome-llm-observability · 45 stars · license a license file GitHub does not identify · pushed 2026-11-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_b4ywyffzjjzwkrys GET https://markdownregistry.com/api/v1/resolve?ref=contextjet-ai/awesome-llm-observability/add-llm-fallbacks GET https://markdownregistry.com/api/v1/blob/9a65d224bf44d26c1d37145c3397a97eef0781bf931bc0669ffe251321f297fb
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.