fetch_feedFetch and normalize any RSS / Atom / RDF feed by URL. CF-robust: fetches directly and falls back to a proxy if the source blocks the gateway. Use list_feeds first for curated sources.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Feed URL, e.g. "https://news.ycombinator.com/rss". | |
| 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 indicate read-only, idempotent, non-destructive. The description adds behavioral details: normalization and fallback proxy retry. No contradictions.
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 core purpose, no wasted words. Efficient and clear.
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?
With 3 parameters fully described in schema and no output schema, the description covers normalization and fallback behavior. Could mention return format but not essential for a fetch tool with examples.
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 itself documents all parameters. The description does not add new parameter information beyond the examples, meeting 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 clearly states the tool fetches and normalizes any RSS/Atom/RDF feed by URL, specifying the verb and resource. It distinguishes from sibling list_feeds by mentioning curated sources.
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 advises to use list_feeds first for curated sources, providing a when-not-to-use hint. It also mentions CF-robust fallback behavior, but does not compare to read_feed, leaving some ambiguity.
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.
Multiple tools overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, suggest_questions, discover_tools, and validate_claim all route questions to the same underlying data catalog, making it hard to choose the right one. Additionally, several prediction-market tools (polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_edge_tracker, polymarket_kalshi_spread, bet_research) have overlapping purposes around finding and evaluating betting opportunities, requiring deep reading to distinguish.
Many tools follow a clear verb_noun pattern (list_feeds, read_feed, fetch_feed, subscribe, unsubscribe, remember, recall, forget), but the naming is inconsistent overall: 'ask_pipeworx', 'ask_pipeworx_beta', 'ask_pipeworx_grounded', 'polymarket_arbitrage', 'polymarket_edges', 'polymarket_edge_tracker', 'polymarket_fill_risk', 'polymarket_kalshi_spread', and 'bet_research' use varied conventions. The 'pipeworx' prefix is applied inconsistently (ask_pipeworx vs deep_research vs discover_tools), and 'ai_visibility_check' vs 'scan_competitor_ai_presence' are related but not aligned in naming.
34 tools is heavy for a server nominally titled 'Gaming Feeds' — the gaming feed tools (list_feeds, read_feed, fetch_feed) are a tiny minority, while the bulk of the surface is a general-purpose data-research and prediction-market toolkit. The count is not justified by the server's stated purpose, and many tools duplicate or overlap in function.
The gaming-feed domain is trivially complete (list, read, fetch) but is buried within a sprawling general-purpose research platform with significant gaps in its own context: no obvious tool for managing or creating feeds, no clear CRUD for the entity/subscription side beyond subscribe/unsubscribe, and no standalone tool for gaming-specific analysis beyond generic feeds. For the actual dominant purpose (data research), the surface is broad but poorly integrated — e.g., ask_pipeworx_grounded and validate_claim feel redundant, and entity_profile/compare_entities/recent_changes overlap.