list_feedsList the curated sports feeds (id, title, category, source). Optionally filter by category (sports) 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: sports. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this as read-only, idempotent, open-world, and non-destructive. The description adds useful behavioral context: feeds are 'curated sports feeds', returns only id/title/category/source, and filters are optional. No contradiction with 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, front-loaded with action and resource, followed by filter options and a handoff to read_feed. Every sentence earns its place with zero filler.
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 two-optional-parameter list tool with strong annotations and no output schema, the description covers purpose, return fields, filtering behavior, and the natural next step. It is fully adequate for an agent to select and invoke correctly.
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% and each parameter already has a clear description. The tool description merely restates that category and keyword are optional filters, adding no significant semantic nuance beyond what the schema 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?
Description uses the specific verb 'List' with the resource 'curated sports feeds' and explicitly enumerates returned fields (id, title, category, source). It clearly distinguishes itself from read_feed by instructing users to pass an id to that tool.
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 states optional filters (category or keyword) and explicitly points to read_feed as the alternative for fetching a single feed by id. This provides clear usage guidance and an alternative, meeting the highest bar for this dimension.
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.
Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded differ only in mode, and the polymarket_* cluster (polymarket_edges, polymarket_edge_tracker, polymarket_arbitrage, polymarket_fill_risk, polymarket_kalshi_spread) all target prediction-market analysis with fuzzy boundaries. The presence of ai_visibility_check and scan_competitor_ai_presence, plus discover_tools and suggest_questions, adds further ambiguity about which tool to select first.
Names are all snake_case but follow mixed conventions: verb_noun (list_feeds, read_feed, fetch_feed, validate_claim) coexists with noun_phrase (entity_profile, recent_changes, polymarket_edges) and prefix-grouped names (ask_pipeworx*, polymarket_*). While subgroups are internally consistent, the overall set lacks a unified pattern, though it remains readable.
34 tools is well above the 25+ threshold for too many, and the count is especially inappropriate for a server named 'Sports Feeds' — most tools are generic data-research or meta-tools (subscriptions, memory, feedback, discovery) unrelated to sports feeds. The bloat suggests the server is actually a broad Pipeworx gateway, not a focused sports feeder.
For a sports-feeds server, only list_feeds, read_feed, and fetch_feed address the core domain, and there is no feed search, categorization beyond a simple list, or sports-specific analytics. While the general research surface (SEC, FDA, economics, prediction markets) is fairly comprehensive, it is misaligned with the stated server purpose, leaving the actual sports-feed functionality thin and with obvious gaps.