reduce-llm-cost SKILL.md skillA
reduce-llm-cost 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/reduce-llm-cost@git:20260705.23078bePins git:20260705.23078be 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/reduce-llm-cost/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260705.23078be, committed Jul 5, 2026
- Size
- 3,103 bytes
- Repository stars
- 45
- License
- a license file GitHub does not identify
Use this to cut the cost of an LLM app using observability data. Trigger on "my OpenAI/Anthropic bill is too high", "reduce token usage", "the app is expensive", "optimize LLM cost", "why am I spending so much on the API". Find the expensive spans first (measure), then apply the cheapest wins. Don't guess - the trace tells you where the money goes.
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
# Reduce LLM cost (measure first) Most LLM bills are dominated by a few patterns you can *see* in traces. Measure before optimizing - the biggest cost is rarely where people assume. ## Step 1 - find where the money goes From your observability tool, sort spans by cost (or `input_tokens`). You're looking for: - **The highest-token spans** - usually bloated context or a whole chat history re-sent every turn. - **Retry storms** - the same call repeated N times (rate limits / transient errors) multiplying cost. - **The most-frequent call** × its per-call cost - a cheap call made 10,000×/day beats one expensive call. - **Model overkill** - using a frontier model for a task a small/cheap model handles fine. If you have no cost data yet, add tracing first (see `instrument-llm-observability`) - you can't optimize what you can't see. ## Step 2 - apply wins, cheapest-effort first 1. **Right-size the model.** Route easy calls (classification, extraction, routing) to a small/cheap model; reserve the frontier model for hard reasoning. Biggest lever for most apps. …
Read the whole file at its exact version.
How to install
mdr add contextjet-ai/awesome-llm-observability/reduce-llm-cost@sha256:9a1a9fd3766c243eThe line at the top of this page pins the label git:20260705.23078be, 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_iwpvh643wrl24giw)
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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 (3103 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_iwpvh643wrl24giw GET https://markdownregistry.com/api/v1/resolve?ref=contextjet-ai/awesome-llm-observability/reduce-llm-cost GET https://markdownregistry.com/api/v1/blob/9a1a9fd3766c243e4809610590b1c678c2923f666a9e78877a7e43f590e3c9d4
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.