hero_statsFetch daily win-rate and pick-rate statistics for a Dota 2 hero by numeric hero_id, optionally filtered to a rank bracket (e.g. HERALD, ARCHON, LEGEND, DIVINE, IMMORTAL). Returns matchCount and winCount per day.
| Name | Required | Description | Default |
|---|---|---|---|
| rank | No | ||
| _apiKey | Yes | Your own STRATZ API token (BYO — Pipeworx does not supply one). Free at https://stratz.com/api after Steam sign-in. | |
| hero_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint: true, idempotentHint: true, and destructiveHint: false, so the safety profile is covered. The description adds that the result returns matchCount and winCount per day, which is useful, but it does not elaborate on rate limits, data freshness, or the exact meaning of 'daily'.
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 two sentences, front-loaded with the primary action and resource, and every phrase adds meaningful information. There is no filler or restating of the tool name.
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 stats-fetching tool with three parameters, the description covers the key inputs, optional filter, and return shape. While there is no output schema, mentioning matchCount and winCount per day gives the agent a concrete idea of the result. It is not exhaustive, but it is sufficient for this tool's complexity.
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 only 33%, so the description carries most of the parameter meaning. It explains that hero_id is numeric, that rank is optional and provides example values, and the return fields are tied to the stats being fetched. The main gap is a complete rank enum or case-sensitivity note, but the description compensates well for the sparse schema.
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 uses a specific verb ('Fetch') and resource ('daily win-rate and pick-rate statistics for a Dota 2 hero'), identifies the primary key ('numeric hero_id'), and notes the optional rank filter. This clearly distinguishes it from the sibling 'hero' and 'heroes' tools, which likely cover broader hero data.
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 when to use the tool: when you need daily hero win-rate/pick-rate stats, with an optional rank bracket. However, it does not explicitly state when not to use it or mention alternatives such as 'hero' or 'player_heroes', leaving some routing decisions to the agent.
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 overlapping or intentionally duplicated purposes: ask_pipeworx/ask_pipeworx_beta currently behave identically, and the Polymarket cluster (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_fill_risk, polymarket_kalshi_spread) presents multiple scanners with fuzzy boundaries. The long descriptions help, but the set as a whole is hard to navigate without close reading.
Naming is a mix of bare single nouns (hero, match, meta, remember, forget), snake_case verb-first names (ask_pipeworx, compare_entities, generate_llms_txt), and noun-first compounds (pipeworx_feedback, bet_research, scan_competitor_ai_presence). There is no consistent verb_noun or noun-verb convention across the set.
At 43 tools, the server bundles at least five unrelated domains (Dota 2 stats, Pipeworx data querying, Polymarket analytics, memory, subscriptions, AI visibility). That is far too many for a focused MCP server, and the mix makes the surface feel like a grab bag rather than a purpose-built toolkit.
Each subdomain individually has solid coverage: Dota 2 has heroes/matches/players/tournaments/meta plus a GraphQL fallback, the data layer has discovery + routing + grounding + validation, and memory/subscriptions have full lifecycle operations. The only real gap is cohesion across domains; within each slice there are no obvious dead ends.