Machine-check a cognition claim: recompute the brain from the submitted content and compare against the claimed brain_id and/or content_hash. valid=true iff every claimed identifier matches the deterministic recomputation (VB3).
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | auto | |
| content | Yes | ||
| brain_id | No | ||
| content_hash | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the deterministic recomputation and comparison logic but does not mention side effects, prerequisites, or behavior when no identifiers are provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences effectively convey the core action and success condition. No wasted words, front-loaded with the key verb.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the main logic but lacks details on edge cases (e.g., when no identifiers are provided) and does not reference the output schema that exists, leaving some context incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It clarifies the roles of brain_id and content_hash but does not explain the 'format' parameter or default values, leaving gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb 'verify' and resource 'brain', explaining the verification mechanism (recompute and compare). It distinguishes from siblings like build_brain (creation) and describe_agent (description).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use or not use this tool vs alternatives. The purpose is implied but no when-to-use or exclusion criteria are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct purpose: building a brain, detecting format, describing agent capabilities, and verifying claims. No overlapping functionality.
All tool names follow a consistent verb_noun snake_case pattern (build_brain, describe_agent, detect_format, verify_brain).
Four tools is well-scoped for the domain of agent file compilation and verification. Each tool earns its place with a distinct action.
The tool surface covers detection, compilation, description, and verification of agent files, forming a complete lifecycle for the domain.