Cito API

match_details

Read-only

Deep match package: optional timelines, advanced stats, live state/snapshots, full map/game tree, media inventory.

When to use:

Analyst deep dive
Live in-game window (LoL/CS2/UFC)
Full demo list

Prefer over match_summary only when summary is insufficient. Prefer match_summary for short answers and default cards.

Do not use when: first-pass live board (use live_matches + match_summary).

Section selection: pass includeTimeline / includeLiveState / includeAdvanced booleans, OR an explicit sections[] list. UFC betting lines: sections:["odds"] (opt-in, never in the default set). If sections[] is non-empty it wins (booleans are ignored). LoL liveState/advanced require gameId.

Parallel-safe: yes. Upstream cost: 1–8 (section-gated). Example: { "game": "lol", "matchId": "lol-match-1", "includeTimeline": true, "includeLiveState": false }

Input Schema

TableJSON Schema

Name	Required	Description
`game`	Yes	Game title: lol \| cs2 \| dota2 \| cod \| ufc \| tennis. Example: "cs2".
`gameId`	No	LoL per-game live window target when distinct from matchId.
`matchId`	Yes	Game-native match id (UFC boutId).
`sections`	No	Explicit section list; defaults to base+playerStats+gamesOrMaps+media. "odds" (UFC) is opt-in: moneyline summarised per fighter with bookmaker count, best and median American price and implied probability, plus a count of every other market. Closing lines for a finished fight come back with currentlyOffered=false rather than being omitted.
`includeAdvanced`	No	Include advanced packages when available (LoL).
`includeTimeline`	No	Include timeline section (heavy).
`includeLiveState`	No	Include live state/snapshots.

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes	true if the tool succeeded
`data`	No	Result payload when ok is true; null on error
`meta`	Yes
`error`	No
`partial`	No
`pagination`	No

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed2 schema fields changedSep 3, 2026

changedInput schema / properties / sections / description

Previous value: -"Explicit section list; defaults to base+playerStats+gamesOrMaps+media."New value: +"Explicit section list; defaults to base+playerStats+gamesOrMaps+media. \"odds\" (UFC) is opt-in: moneyline summarised per fighter with bookmaker count, best and median American price and implied probability, plus a count of every other market. Closing lines for a finished fight come back with currentlyOffered=false rather than being omitted."

changedInput schema / properties / sections / items / enum

Previous value: -[
-  "base",
-  "playerStats",
-  "gamesOrMaps",
-  "timeline",
-  "liveState",
-  "media",
-  "advanced"
-]New value: +[
+  "base",
+  "playerStats",
+  "gamesOrMaps",
+  "timeline",
+  "liveState",
+  "media",
+  "advanced",
+  "odds"
+]

First observedSep 1, 2026

TDQS

A5/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnly/openWorld annotations, the description discloses non-obvious behavior: section precedence ('If sections[] is non-empty it wins'), per-game requirements ('LoL liveState/advanced require gameId'), opt-in odds, parallel safety, and upstream cost range. These are exactly the behavioral details an agent needs to call it correctly and safely.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is organized into scannable labeled blocks (When to use, Prefer, Do not use, Section selection, Parallel-safe), front-loading the core purpose and then diving into edge cases. No filler: every sentence conveys a distinct, decision-relevant fact, and the JSON example at the end is a useful concrete anchor.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 7 parameters, an output schema, and sibling alternatives, the description covers the purpose, usage boundaries, parameter interplay, special cases, and cost behavior. The presence of an output schema means the return-format burden is lifted, and the description fills all selection and invocation gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, yet the description still adds semantic value by explaining how the booleans interact with sections[], which sections are defaults, that odds are opt-in, and what gameId is needed for. The example input further clarifies parameter usage in context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Deep match package: optional timelines, advanced stats, live state/snapshots, full map/game tree, media inventory,' which names the exact resource and scope of the tool. It also explicitly contrasts with match_summary, giving the agent a clear way to distinguish this tool from a key sibling before inspecting schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'When to use' bullets list concrete analyst and live-window scenarios, and the description explicitly states when to prefer match_summary and when to avoid this tool ('first-pass live board (use live_matches + match_summary)'). This is textbook alternative selection guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.5/5.0

Disambiguation5/5

Each tool has a clearly distinct job, and the descriptions explicitly separate temporal states (live vs upcoming vs preview vs recap vs deep-dive) and interaction modes (one-best resolve vs browse search, curated tool vs raw escape hatch). Even the match/event families are carefully tiered so an agent should rarely misselect.

Naming Consistency3/5

Names are readable and grouped into recognizable families like list_*, match_*, and *_profile, but the overall convention is mixed: verb-prefixed names like resolve_entity and call_api sit alongside noun-phrase names like event_card, match_summary, and standings. Consistent snake_case prevents chaos, but there is no uniform verb_noun pattern.

Tool Count4/5

16 tools is at the upper edge of the ideal range, but the server spans multiple games and several composite read workflows, so each tool has a distinct purpose. It feels slightly heavy but not bloated.

Completeness4/5

The set covers health, discovery, entity resolution, profiles, standings, schedules, live matches, previews, recaps, and deep-dive match data, with call_api as an escape hatch for long-tail routes. Notable omissions like a standalone historical results search and some per-game upstream gaps keep it from a perfect score.

Resources

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