read_feedRead a curated food & dining 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. |
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. The description adds that the tool returns normalized items with specific fields (title, link, published, summary) and supports optional keyword filtering—information not present in the annotations and useful for downstream processing.
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 exactly two sentences, with the primary action stated upfront. Every clause carries information: the id source, the return format, and the optional filter. No wasted words or repetition of schema details.
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?
This is a simple, low-complexity read tool with all parameters documented in the schema. The description covers the resource identity, return type, and an optional behavior. There is no output schema, so the explicitly listed return fields (title, link, published, summary) fill that gap adequately.
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?
The input schema already provides descriptions for all three parameters (100% coverage), including the fact that 'feed' comes from list_feeds. The description adds minimal extra semantics beyond a general 'keyword filter' phrase, so it does not elevate above the schema-driven baseline.
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 opens with a specific verb ('Read') and a specific resource ('curated food & dining feed'), and clarifies the identifier source ('from list_feeds'). This distinguishes it from siblings like fetch_feed by domain and by the fact that it reads a managed feed rather than fetching arbitrary URLs.
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 implies a workflow: first call list_feeds to obtain the id, then read_feed. It does not explicitly name alternatives or state when not to use it, but the clear prerequisite ('from list_feeds') gives the agent enough contextual guidance for typical selection.
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.
Many tools have overlapping functionality (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and the set includes both food-specific feeds and general data tools without clear separation. Distinguishing between them, especially for an agent, would be difficult.
Tool names follow no consistent pattern: some are snake_case (list_feeds, read_feed), others are lowercase with underscores (ai_visibility_check), and many are multi-word without clear structure (polymarket_arbitrage, scan_dependency). This inconsistency makes it hard to predict tool names.
With 34 tools, the count is high, and most tools are unrelated to the server's stated purpose of 'Food Feeds'. The inclusion of general-purpose Pipeworx tools (e.g., deep_research, entity_profile, polymarket tools) makes the set bloated and unfocused.
For the food feeds domain, only three tools (list_feeds, read_feed, fetch_feed) are relevant, which is incomplete. The server lacks tools for searching, subscribing, or managing feeds. The presence of many unrelated tools does not compensate for this gap.