Get article
get_articleFetch the full record for an article by slug, including body_text + audio_url.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
get_articleFetch the full record for an article by slug, including body_text + audio_url.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety traits. The description adds that the record includes body_text and audio_url, which is useful return-content context beyond the annotations, but does not disclose any additional behavioral traits like error handling or rate limits. This aligns with the 'annotations present' baseline.
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 a single, well-structured sentence that is immediately clear and front-loaded. Every word adds value, with no filler or redundant phrasing.
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?
Given the tool's simplicity (1 parameter) and the presence of annotations covering safety, the description is largely complete. It mentions the key return fields (body_text + audio_url) despite no output schema. It does not describe error behavior or edge cases, but for a straightforward fetch tool, this is sufficient.
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 0%, so the description must compensate. It only mentions 'by slug', which essentially repeats the parameter name without adding meaning (e.g., format, example, or what a slug is). With no other context, the description fails to enrich the parameter beyond its name.
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 uses the specific verb 'Fetch' and identifies the resource ('article') and the key identifier ('by slug'). It also lists key fields returned ('body_text + audio_url'), which clearly distinguishes it from sibling tools like search_articles (which searches) and get_audio_url (which returns only a URL).
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 clearly implies use when you have a slug and need the full article record. No explicit exclusions or alternatives are named, but the context is unambiguous. A score of 4 is appropriate because it provides clear context without explicit when-not guidance.
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.
Every tool has a clearly distinct purpose, with detailed descriptions that prevent ambiguity. Even similar tools like search_articles, search_declassified, and search_unified target different corpora, and the publisher tools are well-separated. No overlap that would confuse an agent.
All tool names follow a consistent verb_noun pattern with snake_case, using clear prefixes like get_, search_, subscribe_, publisher_, fm_, digest_, etc. The naming is predictable and systematic, making it easy for an agent to infer functionality.
At 37 tools, the count is higher than the typical 3-15 range for a coherent set, but the server covers a wide domain (content retrieval, podcast management, fund manager book, embedder network, etc.). Each tool earns its place, though the set could be slightly reduced by merging some rare-use tools.
The tool surface is comprehensive for the server's purpose—search, audio, subscriptions, publisher workflows, and special features like the Divergence Index. Minor gaps exist (e.g., no explicit unsubscribe tool, no article update/delete), but they are not critical for core workflows.