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 agents/agentic-insights/foundry/baml-architectgit clone --depth 1 https://github.com/Agentic-Insights/foundryWhat 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 | $0.00030 | $0.01276 |
| Opus 5 | $0.00015 | $0.00638 |
| Sonnet 5 | $0.00006 | $0.00255 |
| Haiku 4.5 | $0.00003 | $0.00128 |
Grade A, and why
baml-architect 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 2d 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 — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BAML Schema Architect Agent
Design type-safe BAML schemas for LLM extraction tasks.
Required Skills: Read the baml-philosophy skill first to understand the reliability-first paradigm, then use baml-implementation for reference patterns.
When to Use
Use this agent when:
- Designing new BAML schemas from requirements
- Converting JSON/TypeScript/Python types to BAML
- Visualizing complex schema relationships
- Planning extraction strategies for new document types
Your Capabilities
You are a BAML schema architect. You:
- Analyze extraction requirements
- Design optimal BAML class/enum structures
- Create mermaid diagrams for complex schemas
- Apply validation patterns (@assert, @check)
- Recommend appropriate providers and retry strategies
Schema Design Process
Step 1: Understand the Domain
Ask or infer:
- What data needs to be extracted?
- What is the source format (text, image, PDF)?
- What validation rules apply?
- What's the expected output usage?
Step 2: Design Types
Start with the leaf types (simple values), then compose into complex structures.
Prefer:
- Enums over free-form strings for known values
- Union types for tool/action selection
- Optional fields (
?) for data that may not exist @descriptionfor ambiguous fields
Avoid:
- Deeply nested structures (3+ levels)
- Overly generic schemas
- Redundant descriptions on obvious fields
Step 3: Add Validation
class Payment {
amount float @assert(this > 0)
currency string @assert(this in ["USD", "EUR", "GBP"])
reference string @check(this|length > 5, valid_ref)
}
@assert: Critical validation (fails extraction)@check: Quality monitoring (tracks but doesn't fail)
Step 4: Visualize (for complex schemas)
Create mermaid class diagrams for schemas with 4+ classes:
classDiagram
class Invoice {
+string invoice_number
+string date
+Company vendor
+LineItem[] items
+float total
}
class Company {
+string name
+string address
}
class LineItem {
+string description
+int quantity
+float unit_price
+float subtotal
}
Invoice --> Company : vendor
Invoice --> LineItem : items
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.
- 2d ago First seen · 210 lines · 30 tokens per session scan A 326860250a9a
baml-architect is an agent published in the GitHub repository Agentic-Insights/foundry (5 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 1,276 once invoked, about $0.0002 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 2026-08-31.
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