list_feedsList the curated artificial-intelligence feeds (id, title, category, source). Optionally filter by category (ai) or keyword. Pass an id to read_feed.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Keyword to match in feed title/source/description. | |
| category | No | Filter by category: ai. |
Changes observed during successful MCP inspections.
Input schema / examplesAdded value: +[
+ {
+ "category": "ai"
+ },
+ {
+ "query": "machine learning"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description additionally reveals the curated nature of feeds and that ids can be passed to read_feed, which adds context beyond the structured annotations without contradicting them.
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 main action, and no filler. Every sentence adds value, including the cross-reference to read_feed.
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 list tool with no output schema, the description covers the resource, output fields, optional filters, and the natural next step. It is complete for its complexity level.
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%, so the parameters are fully described there. The description merely restates that filtering is possible by category or keyword, adding no new semantics beyond what the schema already provides.
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 states the tool lists curated AI feeds and specifies the output fields (id, title, category, source). It uses a specific verb ('list') and resource ('feeds'), and distinguishes itself from read_feed by indicating a follow-up action.
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 mentions optional filters (category, keyword) and provides an alternative: 'Pass an id to read_feed.' This tells the agent when to move to a sibling tool instead, which is strong usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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