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 skills add ronmkr/PromptBook --skill agnostic-model-connectorgit clone --depth 1 https://github.com/ronmkr/PromptBookWrote 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/ronmkr/promptbook/agnostic-model-connector)<a href="https://agentmods.dev/skills/ronmkr/promptbook/agnostic-model-connector"><img src="https://agentmods.dev/badge/skills/ronmkr/promptbook/agnostic-model-connector/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ronmkr/promptbook/agnostic-model-connector"><img src="https://agentmods.dev/badge/skills/ronmkr/promptbook/agnostic-model-connector.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00174 | $0.08007 |
| Opus 5 | $0.00087 | $0.04004 |
| Sonnet 5 | $0.00035 | $0.01601 |
| Haiku 4.5 | $0.00017 | $0.00801 |
Grade A, and why
agnostic-model-connector scanned grade A with 1 finding 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 7d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
2. **Raw HTTP** (`curl`, `requests`, `fetch`, `httpx`, etc.) — only when the user explicitly asks for cURL/REST/raw HTTP, the project is a shell/cURL project, or the language has no official SDK. How it starts
The opening of the file, as written. The whole thing — 324 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Building LLM-Powered Applications with The Agent
This skill helps you build LLM-powered applications with The Agent. Choose the right surface based on your needs, detect the project language, then read the relevant language-specific documentation.
Before You Start
Scan the target file (or, if no target file, the prompt and project) for non-The Provider provider markers — import openai, from openai, langchain_openai, OpenAI(, gpt-4, gpt-5, file names like agent-openai.py or *-generic.py, or any explicit instruction to keep the code provider-neutral. If you find any, stop and tell the user that this skill produces The Agent/Universal SDK code; ask whether they want to switch the file to The Agent or want a non-The Agent implementation. Do not edit a non-The Provider file with Universal SDK calls.
Output Requirement
When the user asks you to add, modify, or implement a The Agent feature, your code must call The Agent through one of:
- The official Universal SDK for the project's language (
google-generativeai,@google/generative-ai,com.google.generativeai.*, etc.). This is the default whenever a supported SDK exists for the project. - Raw HTTP (
curl,requests,fetch,httpx, etc.) — only when the user explicitly asks for cURL/REST/raw HTTP, the project is a shell/cURL project, or the language has no official SDK.
Never mix the two — don't reach for requests/fetch in a Python or TypeScript project just because it feels lighter. Never fall back to OpenAI-compatible shims.
Never guess SDK usage. Function names, class names, namespaces, method signatures, and import paths must come from explicit documentation — either the {lang}/ files in this skill or the official SDK repositories or documentation links listed in shared/live-sources.md. If the binding you need is not explicitly documented in the skill files, WebFetch the relevant SDK repo from shared/live-sources.md before writing code. Do not infer Ruby/Java/Go/PHP/C# APIs from cURL shapes or from another language's SDK.
What ships with it
44 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.
- csharp/gemini-api.md 14 KB
- curl/examples.md 6.3 KB
- curl/managed-agents.md 7.3 KB
- go/gemini-api.md 15 KB
- go/managed-agents/README.md 19 KB
- java/gemini-api.md 15 KB
- java/managed-agents/README.md 17 KB
- LICENSE.txt 11 KB
- php/gemini-api.md 11 KB
- php/managed-agents/README.md 13 KB
- python/gemini-api/batches.md 5.1 KB
- python/gemini-api/files-api.md 4.0 KB
- python/gemini-api/README.md 12 KB
- python/gemini-api/streaming.md 5.2 KB
- python/gemini-api/tool-use.md 17 KB
- python/managed-agents/README.md 9.6 KB
- ruby/gemini-api.md 2.9 KB
- ruby/managed-agents/README.md 10.0 KB
- shared/agent-design.md 8.2 KB
- shared/error-codes.md 7.6 KB
- shared/live-sources.md 17 KB
- shared/managed-agents-api-reference.md 24 KB
- shared/managed-agents-client-patterns.md 9.2 KB
- shared/managed-agents-core.md 14 KB
- shared/managed-agents-environments.md 11 KB
- shared/managed-agents-events.md 9.4 KB
- shared/managed-agents-memory.md 9.4 KB
- shared/managed-agents-multiagent.md 6.4 KB
- shared/managed-agents-onboarding.md 8.1 KB
- shared/managed-agents-outcomes.md 6.0 KB
- shared/managed-agents-overview.md 9.6 KB
- shared/managed-agents-self-hosted-sandboxes.md 9.8 KB
- shared/managed-agents-tools.md 14 KB
- shared/managed-agents-webhooks.md 5.0 KB
- shared/model-migration.md 79 KB
- shared/models.md 8.1 KB
- shared/prompt-caching.md 9.6 KB
- shared/tool-use-concepts.md 17 KB
- typescript/gemini-api/batches.md 2.6 KB
- typescript/gemini-api/files-api.md 2.2 KB
- typescript/gemini-api/README.md 9.8 KB
- typescript/gemini-api/streaming.md 5.5 KB
- typescript/gemini-api/tool-use.md 15 KB
- typescript/managed-agents/README.md 9.2 KB
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.
- 7d ago First seen · 324 lines · 174 tokens per session scan A 156bc8a95040
agnostic-model-connector is a skill published in the GitHub repository ronmkr/PromptBook (2 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 174 tokens to every session and 8,007 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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