List Deep Dives series and their parts (free parts are public; later parts need Premium). Metadata only; read a part with get_lesson.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No | Optional fallback: your agent_signup token or paired agent key, only if your MCP client can't send an Authorization: Bearer header (the header is preferred and wins). Treated exactly like the header; never shown back. |
Changes observed during successful MCP inspections.
Input schema / properties / tokenAdded value: +{
+ "description": "Optional fallback: your agent_signup token or paired agent key, only if your MCP client can't send an Authorization: Bearer header (the header is preferred and wins). Treated exactly like the header; never shown back.",
+ "maxLength": 200,
+ "minLength": 1,
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly/idempotent/non-destructive/closed-world, so the safety profile is covered. The description adds genuinely new behavioral context: results are metadata only (no lesson content is returned) and later parts are gated behind Premium, which affects what an agent will actually receive.
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 short sentences with zero filler, and the most decision-relevant facts (what is listed, metadata only, where to go for content) are front-loaded.
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?
No output schema exists, and the description adequately compensates by saying the result is metadata only and is subject to the free/Premium split. It does not describe ordering, pagination, or the shape of a series/parts entry, which is a minor residual gap.
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 description coverage is 100% and the single token parameter is fully documented in the schema itself. The description adds no further parameter guidance, so the baseline of 3 applies.
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?
States a specific verb (List) and resource (Deep Dives series and their parts), and instantly separates itself from the sibling get_lesson by declaring it is metadata only. An agent can tell what this returns versus what get_lesson returns without opening either schema.
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?
Explicitly routes content retrieval to get_lesson ("read a part with get_lesson") and explains the free/Premium split that governs access. No explicit when-not-to-use-this-tool case, but the alternative and the entitlement condition are both stated.
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.