matchFetch full details of a single Dota 2 match by numeric match id — duration, start time, Radiant/Dire teams, game mode, lobby type, and per-player stats (heroId, K/D/A, GPM, XPM, level).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| _apiKey | Yes | Your own STRATZ API token (BYO — Pipeworx does not supply one). Free at https://stratz.com/api after Steam sign-in. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so no contradiction exists. The description adds value by stating exactly what is fetched (duration, teams, game mode, per-player stats), which is behaviorally relevant when invoking the tool.
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?
A single well-structured sentence front-loads the action and resource, then lists returned fields in a compact, readable list. No filler 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?
With no output schema, the description's list of returned fields gives an agent a good sense of the response. It does not mention API-key requirements or error behavior, but those are covered by the schema and the tool's read-only annotations, so the definition is largely complete.
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 only 50%, but the description compensates for the undocumented 'id' parameter by clarifying it is the numeric Dota 2 match identifier. The other parameter, _apiKey, is already fully explained in the schema, so the description meaningfully covers the gap.
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 names a specific action ('Fetch full details') and a clear resource ('a single Dota 2 match by numeric match id'), then lists the key data returned. This distinguishes it from list-like siblings such as player_matches and live_matches.
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 phrase 'by numeric match id' and 'single match' make the intended invocation context clear: an agent should use this when it already has one numeric Dota 2 match id. It does not explicitly name alternatives or exclusions, so it stops short of a 5.
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.