Given a post that is part of a numbered multi-part series (e.g. "Part I/II/III"), return the ENTIRE series in reading order. Use this to read an arc start-to-finish instead of guessing part numbers. Returns null-ish empty when the post is standalone.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | A post ID or slug belonging to the series |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds useful behavioral context: results are ordered in reading order, and the tool returns null-ish empty for standalone posts. This goes beyond the annotation without contradicting it.
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, front-loaded with the core purpose, and no wasted words. The edge case is covered efficiently.
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?
For a simple read-only tool with one parameter and no output schema, the description fully conveys input, output behavior, and the standalone edge case. No additional context is needed.
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 100% and the parameter description already says 'A post ID or slug belonging to the series.' The tool description adds little beyond restating that the input is a post in the series, so a 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 states a specific verb ('return'), a clear resource (the entire multi-part series), and the input type (a post in that series). It also distinguishes itself from siblings like get_blog_post by highlighting that it returns the full series in reading order, not just a single post.
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?
It explicitly says to use this tool to read an arc start-to-finish instead of guessing part numbers, and notes that standalone posts yield a null-ish empty result. However, it does not name specific alternative tools, so it stops short of a 5.
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.