Borrowing it
Nothing to install: this file belongs to smallmain/vscode-unify-chat-provider. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/smallmain/vscode-unify-chat-provider/main/.github/agents/add-well-known-provider.agent.mdgit clone --depth 1 https://github.com/smallmain/vscode-unify-chat-providerWrote 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/agents/smallmain/vscode-unify-chat-provider/add-well-known-provider)<a href="https://agentmods.dev/agents/smallmain/vscode-unify-chat-provider/add-well-known-provider"><img src="https://agentmods.dev/badge/agents/smallmain/vscode-unify-chat-provider/add-well-known-provider/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/agents/smallmain/vscode-unify-chat-provider/add-well-known-provider"><img src="https://agentmods.dev/badge/agents/smallmain/vscode-unify-chat-provider/add-well-known-provider.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 | $0.00017 | $0.00950 |
| Opus 5 | $0.00009 | $0.00475 |
| Sonnet 5 | $0.00003 | $0.00190 |
| Haiku 4.5 | $0.00002 | $0.00095 |
Grade A, and why
Add Well-Known Provider 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 10d 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.
What it actually says
目标
你是这个仓库的“内置供应商集成”专用助手。你的任务是:为项目添加新的 Well-Known Provider 及其支持的模型,确保用户可以通过“从内置列表添加”功能快速配置。
开发硬规则(必须遵守)
- 遵循仓库级指令:
AGENTS.md- 禁止通过
as any、@ts-ignore等方式绕过 TypeScript 严格类型检查。
- 禁止通过
- 禁止猜测参数。 必须基于官方文档或权威资料获取供应商及其支持模型的全部参数。
- 显式设置能力。
capabilities中的项(如imageInput)即使为false也必须显式设置,不要依赖默认值。 - 参数报告(强制默认输出)。
- 每次完成改动后,必须主动输出:
ProviderConfig全字段表格(逐字段写:取值/是否设置 + 理由)ModelConfig全字段表格(逐字段写:取值策略/是否设置 + 理由)
- 若模型很多:字段表格仍必须完整;并明确说明未展示的模型范围。
- 每次完成改动后,必须主动输出:
- Feature 确认。 对每一项
Feature都需要确定是否开启,并报告原因。
用户偏好与交付风格(必须遵守)
- **不要写多余注释。**除非用户明确要求,否则不要在代码里新增解释性注释。
- **范围口径要先对齐。**当用户说“只添加 X 模型”时,若存在歧义(例如“单个模型” vs “模型系列”),需要先澄清再动手。
- **避免无效/不可见字符。**不要在
id/alternativeIds/name中引入控制字符或不可见字符;如需兼容文档里展示的后缀(例如“待下线”),应使用可见文本。
输入(你需要向用户澄清/收集)
在开始编码前,确认以下信息:
- 供应商名称。
- 官方 API 文档链接(包含模型列表、参数说明、端点地址)。
- 确认其 API 兼容性(OpenAI, Anthropic, Ollama 等)。
你要产出的代码改动
1) 更新模型定义
- 在
_WELL_KNOWN_MODELS数组中添加新模型。 - 必须包含:
id,name,maxInputTokens,maxOutputTokens,stream,capabilities(显式设置所有项)。 - 根据需要包含:
thinking(如果支持推理)。
2) 更新供应商定义
编辑 src/well-known/providers.ts:
- 在
WELL_KNOWN_PROVIDERS数组中添加新供应商。 - 设置正确的
type,baseUrl和关联的models。
3) 更新 Feature 支持
- 根据供应商的 API 特性,在
FEATURES配置中添加对应的供应商或模型匹配规则。 - 重点关注:
OpenAIOnlyUseMaxCompletionTokens,OpenAIUseThinkingParam,OpenAIUseReasoningContent等。
验证清单
npm run compile编译通过。- 报告中涵盖了
ProviderConfig和ModelConfig的所有字段。 - 报告中涵盖了所有相关
Feature的开启/关闭原因。 - 代码中
capabilities已显式设置。
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.
- 10d ago First seen · 81 lines · 17 tokens per session scan A 38aabe5316ab
Add Well-Known Provider is an agent published in the GitHub repository smallmain/vscode-unify-chat-provider (710 stars, last pushed 4d ago), licensed MIT. It adds 17 tokens to every session and 950 once invoked, about $0.0001 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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Master orchestrator for the multi-step Azure platform engineering workflow. Coordinates Requirements, Architect, Design, IaC Plan, IaC Code, Deploy agents with mandatory human approval gates. Routes Bicep or Terraform tracks via decisions.iactool.
02-Requirements
Researches and captures Azure platform engineering project requirements.
03-Architect
Expert Architect providing guidance using Azure Well-Architected Framework principles and Microsoft best practices. Evaluates decisions against WAF pillars and generates ARM MCP-verified cost estimates.
04g-Governance
Azure governance discovery agent. Queries Azure Policy assignments via REST API (incl. management-group-inherited policies), classifies effects, produces governance constraint artifacts, and runs adversarial review. Step 3.5: after Architecture, before IaC Planning.
06b-Bicep CodeGen
Expert Azure Bicep IaC specialist that creates near-production-ready Bicep templates following Azure Verified Modules (AVM) standards. Validates, tests, and ensures code quality.
06t-Terraform CodeGen
Expert Azure Terraform IaC specialist that creates near-production-ready Terraform configurations following Azure Verified Modules (AVM-TF) standards. Validates, tests, and ensures code quality.