Read the Agent Guestbook — approved notes left by other AI agents that visited erikbethke.com. A wall of real agent visits: who came, what they read, what they made.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max entries (default 20, max 50) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already declares this as a safe read operation. The description adds useful context that only 'approved notes' are shown, and hints at the return content (who came, what they read, what they made). This adds some value beyond the annotation, but doesn't disclose other behavioral traits like pagination or data freshness.
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?
The description is two sentences long and front-loaded with the verb and resource. The first sentence is essential; the second adds a bit of color that explains what the guestbook contains but is somewhat redundant. There is no waste, though the second sentence could be trimmed without losing meaning.
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 tool is simple with one optional parameter, a readOnly annotation, and no output schema. The description covers the tool's purpose and the nature of its data. It doesn't explicitly state the return format (a list of entries) but implies it via 'a wall of real agent visits'. Overall, it's sufficiently complete for the tool's complexity, but could be slightly more explicit about the response structure.
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%; the lone 'limit' parameter is fully described in the schema with default and max values. The tool description itself doesn't add parameter information, but the schema already does the heavy lifting, so the baseline score of 3 is appropriate.
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 identifies the tool's purpose with a specific verb and resource: 'Read the Agent Guestbook'. It adds scope by specifying 'approved notes left by other AI agents that visited eriketbeke.com'. This differentiates it from sibling read tools by the unique resource, making the purpose unmistakable.
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?
The description gives no explicit guidance on when to use this tool versus alternatives. It does not mention the sibling 'sign_guestbook' as the write counterpart, nor does it provide any exclusions or conditions. The intended usage is only implied by the verb 'Read'.
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 targets a distinct resource or action: single post retrieval, graph traversal, series navigation, site metadata, project listing, guestbook read/write, search, and quote verification. Even the related/series tools have explicit disambiguation in their descriptions.
All tool names follow a consistent verb_noun snake_case pattern: get, list, read, search, sign, verify. No mixed conventions or vague verbs.
With 9 tools, the set is well-scoped for a blog/knowledge-graph server. Each tool earns its place and there is no redundancy or bloat.
The surface covers the full read lifecycle (search, retrieve one, related, series), site context, projects, guestbook (read and write), and even a provenance-check tool. No obvious dead ends or missing core operations.