Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/bitsky-tech/amphiloop/bridgic-llmsnpx skills add bitsky-tech/AmphiLoop --skill bridgic-llmsgit clone --depth 1 https://github.com/bitsky-tech/AmphiLoopWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/bitsky-tech/amphiloop/bridgic-llms)<a href="https://agentmods.dev/skills/bitsky-tech/amphiloop/bridgic-llms"><img src="https://agentmods.dev/badge/skills/bitsky-tech/amphiloop/bridgic-llms.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00091 | $0.00868 |
| Opus 5 | $0.00046 | $0.00434 |
| Sonnet 5 | $0.00018 | $0.00174 |
| Haiku 4.5 | $0.00009 | $0.00087 |
Grade A, and why
bridgic-llms scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bridgic LLMs
Model-neutral LLM integration with protocol-driven capability declaration.
Dependencies
| Package | BaseLlm |
StructuredOutput |
ToolSelection |
|---|---|---|---|
bridgic-llms-openai |
yes | yes | yes |
bridgic-llms-openai-like |
yes | no | no |
bridgic-llms-vllm |
yes | yes | yes |
python-dotenv |
— | — | — |
Install only the LLM provider package you need. python-dotenv is required for loading .env configuration.
Installation: Run the install script to set up all dependencies:
bash "skills/bridgic-llms/scripts/install-deps.sh" "$PWD" [PROVIDER]
Supported providers: openai (default), openai-like, vllm. The script checks uv availability, initializes a uv project if needed, installs any missing packages via uv add, and runs uv sync to finalize the environment. When it exits successfully the project is fully initialized and ready to use — no manual uv add / uv sync follow-up is required.
Quick Start
import os
from dotenv import load_dotenv
from bridgic.llms.openai import OpenAILlm, OpenAIConfiguration
load_dotenv()
llm = OpenAILlm(
api_key=os.environ.get("LLM_API_KEY"),
api_base=os.environ.get("LLM_API_BASE"),
configuration=OpenAIConfiguration(
model=os.environ.get("LLM_MODEL", "gpt-4o"),
temperature=0.0,
max_tokens=16384,
),
timeout=180.0,
)
Provider Selection Guide
| Provider | When to Use |
|---|---|
OpenAILlm |
Production use, need structured output or tool calling. Works with OpenAI API. |
OpenAILikeLlm |
Third-party OpenAI-compatible APIs (DashScope, etc.), only need basic chat/stream. |
VllmServerLlm |
Self-hosted vLLM inference server, full capability. |
Common pitfall: Do NOT use OpenAILikeLlm when you need structured output or tool selection — it does not implement those protocols. Use OpenAILlm instead.
Basic Interfaces
All providers implement BaseLlm:
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 98 lines · 91 tokens per session scan A a4f37ad8bd4d
bridgic-llms is a skill published in the GitHub repository bitsky-tech/AmphiLoop (68 stars, last pushed 3mo ago), licensed MIT. It adds 91 tokens to every session and 868 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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