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 Agentic-Insights/foundry --skill baml-codegengit clone --depth 1 https://github.com/Agentic-Insights/foundryWrote 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/agentic-insights/foundry/baml-codegen)<a href="https://agentmods.dev/skills/agentic-insights/foundry/baml-codegen"><img src="https://agentmods.dev/badge/skills/agentic-insights/foundry/baml-codegen/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/agentic-insights/foundry/baml-codegen"><img src="https://agentmods.dev/badge/skills/agentic-insights/foundry/baml-codegen.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 | $0.00100 | $0.01241 |
| Opus 5.5 | $0.00040 | $0.00496 |
| Sonnet 5.5 | $0.00020 | $0.00248 |
| Haiku 4.5 | $0.00010 | $0.00124 |
Grade A, and why
baml-codegen 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 1mo 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BAML Code Generation
Generate type-safe LLM extraction code. Use when creating structured outputs, classification, RAG, or agent workflows.
Golden Rules
- NEVER edit
baml_client/- 100% generated, overwritten on everybaml-cli generate; checkbaml_src/generators.bamlforoutput_type(python, typescript, ruby, go) - ALWAYS edit
baml_src/- Source of truth for all BAML code - Run
baml-cli generateafter changes - Regenerates typed client code for target language
Philosophy (TL;DR)
- Schema Is The Prompt - Define data models first, compiler injects types
- Types Over Strings - Use enums/classes/unions, not string parsing
- Fuzzy Parsing Is BAML's Job - BAML extracts valid JSON from messy LLM output
- Transpiler Not Library - Write
.baml→ generate native code (Python/TypeScript/Ruby/Go), no runtime dependency - Test-Driven Prompting - Use VS Code playground or
baml-cli testto iterate
Workflow
Analyze → Pattern Match (MCP) → Validate → Generate → Test → Deliver
↓ [IF ERRORS] Error Recovery (MCP) → Retry
BAML Syntax
| Element | Example |
|---|---|
| Class | class Invoice { total float @description("Amount") @assert(this > 0) @alias("amt") } |
| Enum | enum Category { Tech @alias("technology") @description("Tech sector"), Finance, Other } |
| Function | function Extract(text: string, img: image?) -> Invoice { client GPT5 prompt #"{{ text }} {{ img }} {{ ctx.output_format }}"# } |
| Client | client<llm> GPT5 { provider openai options { model gpt-5 } retry_policy Exponential } |
| Fallback | client<llm> Resilient { provider fallback options { strategy [FastModel, SlowModel] } } |
Types
- Primitives:
string,int,float,bool| Multimodal:image,audio - Containers:
Type[](array),Type?(optional),map<string, Type>(key-value) - Composite:
Type1 | Type2(union), nested classes - Annotations:
@description("..."),@assert(condition),@alias("json_name"),@check(name, condition)
What ships with it
22 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.
- assets/agents/README.md 395 B
- assets/classification/README.md 443 B
- assets/classification/sentiment_classification.baml 716 B
- assets/extraction/invoice_extraction.baml 1.0 KB
- assets/extraction/README.md 437 B
- assets/integrations/README.md 442 B
- assets/rag/README.md 438 B
- references/advanced-patterns.md 19 KB
- references/BAML-REFERENCE-SOURCE.md 27 KB
- references/examples.md 18 KB
- references/frameworks-langgraph.md 19 KB
- references/languages-other.md 8.0 KB
- references/languages-python.md 13 KB
- references/languages-typescript.md 15 KB
- references/mcp-interface.md 9.9 KB
- references/patterns.md 3.5 KB
- references/philosophy.md 2.2 KB
- references/providers.md 2.9 KB
- references/types-and-schemas.md 3.2 KB
- references/usecase-image-forms.md 4.5 KB
- references/usecase-workflows.md 5.8 KB
- references/validation.md 3.1 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.
- 1mo ago First seen · 91 lines · 100 tokens per session scan A 3705e1cf6958
baml-codegen is a skill published in the GitHub repository Agentic-Insights/foundry (5 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 100 tokens to every session and 1,241 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-31.
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