io.github.labham-llc/agentcents
Local LLM cost proxy: forecasts each call and recommends the cheapest model that clears the task.
Open source Open in the app JSON README (API)
About
Local LLM cost proxy: forecasts each call and recommends the cheapest model that clears the task.
Details
- Kind
- MCP servers
- Topic
- AI, RAG & memory
- Publisher
- labham-llc
- Origin
- official
- Category
- ferramentas
- Transport
- local
- Version
- 1.1.3
- Last push
- 2026-07-24T21:56:41Z
- Repository state
- ativo
- Added
- 2026-08-29 04:00:22
- Updated
- 2026-08-29 04:00:22
- Origin id
io.github.labham-llc/agentcents
README
# agentcents — LLM cost consulting skill for Claude A [Claude Skill](https://agentskills.io) that turns Claude into a neutral LLM cost advisor: estimate what any call or agent workflow will cost across candidate models, get the **cheapest model that clears the task's capability bar**, and see the comparison as a Mermaid diagram — with honest ranges, never false point estimates. Works two ways: - **Consult mode (no install):** answers from a bundled, hand-verified snapshot of current model prices and Intelligence Index scores. - **Live mode:** if the [agentcents](https://pypi.org/project/agentcents/) proxy is running locally, the skill uses your real ledger — calibrated forecasts, spend, and accuracy instead of priors. ## Install **Claude.ai / Desktop:** Settings → Capabilities → Skills → Add → upload this folder (or the packaged `.skill`). **Claude Code:** `/plugin marketplace add labham-llc/agentcents-skill` then `/plugin install agentcents@labham-skills` Then just ask things like: > what would it cost to classify ~500 support emails a day, about 200 tokens each? > > I'm building a 5-step research agent — which model should each step use? ## What's in the box ``` SKILL.md — the consulting method (measure, range, bar, pick, flag instability) assets/pricing.json — price + capability snapshot (see _meta.verified_utc) references/local-api.md — live-mode reference for a locally running agentcents ``` **Snapshot verified: 2026-07-15** (see `_meta.verified_utc`) — refreshed with each agentcents release. ## The product behind it [agentcents](https://labham.com/agentcents.html) is a local proxy that meters, forecasts, and budget-enforces LLM API calls — and grades its own forecasting accuracy on a calibration page. `pip install agentcents`. The skill is free; so is the agentcents free tier. © Labham LLC · skill instructions and snapshot data may be redistributed with attribution; the agentcents software itself is proprietary (see its LICENSE).