read_feedRead a curated artificial-intelligence feed by its id (from list_feeds). Returns normalized items (title, link, published, summary). Optionally filter items by keyword.
| Name | Required | Description | Default |
|---|---|---|---|
| feed | Yes | Curated feed id (from list_feeds). | |
| limit | No | Max items (1-50, default 20). | |
| query | No | Keyword filter over item title/summary. |
Changes observed during successful MCP inspections.
Input schema / examplesPrevious value: -[
- {
- "feed": "arxiv-cs-ai"
- },
- {
- "feed": "hackernews",
- "limit": 10,
- "query": "llm"
- }
-]New value: +[
+ {
+ "feed": "arxiv-cs-ai"
+ },
+ {
+ "feed": "simon-willison",
+ "limit": 10,
+ "query": "AI"
+ }
+]Input schema / examplesAdded value: +[
+ {
+ "feed": "arxiv-cs-ai"
+ },
+ {
+ "feed": "hackernews",
+ "limit": 10,
+ "query": "llm"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds value beyond annotations by specifying that items are normalized and include title, link, published, and summary, which is useful since no output schema exists. Nothing contradicts the annotations.
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 with no filler. The main action and source are front-loaded, followed by the return format and optional filtering, making the description easy to scan and act on.
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 read-only, idempotent tool with all parameters documented in the schema, the description supplies the missing return structure and filtering option. It could add edge-case details like behavior for invalid feed ids or ordering, but those are not required for correct invocation.
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%, so the schema fully documents feed, limit, and query. The description adds only minor value by restating that filtering is optional and that feed ids come from list_feeds, which the schema already says. Baseline 3 is appropriate when the schema carries the parameter documentation burden.
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 verb ('Read'), the resource ('a curated artificial-intelligence feed'), and the scope ('by its id'). It also gives the return shape and mentions filtering, but it does not explicitly differentiate itself from the sibling fetch_feed, so the distinction is inferred rather than stated.
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 clear context by saying the feed id comes from list_feeds and that items can be filtered by keyword. It implies when this tool is appropriate, but it does not state exclusions or name alternatives such as fetch_feed for cases where a curated id is not available.
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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