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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. 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
NameRequiredDescriptionDefault
gameYesGame title: lol | cs2 | dota2 | cod | ufc | tennis. Example: "cs2".
gameIdNoLoL per-game live window target when distinct from matchId.
matchIdYesGame-native match id (UFC boutId).
sectionsNoExplicit section list; defaults to base+playerStats+gamesOrMaps+media.
includeAdvancedNoInclude advanced packages when available (LoL).
includeTimelineNoInclude timeline section (heavy).
includeLiveStateNoInclude live state/snapshots.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYestrue if the tool succeeded
dataNoResult payload when ok is true; null on error
metaYes
errorNo
partialNo
paginationNo

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already indicate read-only, open-world, non-destructive behavior. The description goes further by disclosing non-obvious section precedence (sections[] overrides booleans), the LoL gameId requirement for liveState/advanced, parallel-safety, and upstream cost range. This is valuable behavioral context beyond annotations.

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?

Although longer than average, the description is tightly structured with headers and bullets that serve distinct purposes. Every section adds value: core purpose, use cases, exclusions, selection logic, opeational details, and an example. It remains efficient given the tool's 7-param complexity.

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 complex tool with 7 params, an output schema, and many siblings, this description covers all necessary guidance: when to use, when not to use, section selection semantics, LoL-specific requirements, paralllel-safety, upstream cost, and an inline example. Nothing essential is missing.

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?

The input schema fully describes each parameter, so the baseline is 3. The description adds critical semantics: sections[] wins over booleans, LiveState/advanced require gameId, and section selection options. This significantly clarifies how the parameters interact in practice.

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

Purpose4/5

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

The description clearly frames match_details as a deep match package with optional timelines, advanced stats, live state/snapshots, map/game tree, and media inventory. It is easily distinguishable from match_summary and lighter siblings, though the opening line lacks an explicit verb like 'retrieve' or 'get'.

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 description provides explicit 'When to use' cases, explicitly prefers match_summary for short answers/default cards, and warns against using it for first-pass live boards in favor of live_matches + match_summary. It also explains when to use the booleans versus the sections[] list.

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

A4.6/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose. Composite tools like match_preview, match_summary, and match_details are well-separated by lifecycle stage, and resolve_entity vs search_entities are differentiated by intended use (single best match vs browsing list). No two tools appear to do the same thing.

Naming Consistency4/5

All names follow snake_case and are descriptive, but the pattern is not strictly verb_noun: most retrieval tools use noun phrases (match_summary, team_profile, standings) while actions use verb_noun (call_api, list_capabilities, resolve_entity). This is consistent within each category, so it remains predictable.

Tool Count4/5

16 tools is slightly above the ideal 3-15 range, but the server covers multiple games (LoL, CS2, UFC, Dota, COD, Tennis) and provides composite tools to reduce upstream calls. Each tool earns its place, and the breadth justifies the count.

Completeness5/5

The tool surface covers health checks, live matches, schedules, profiles, standings, head-to-head, previews, recaps, deep match details, event cards, entity resolution, and includes an escape hatch (call_api) for long-tail paths. No obvious gaps for a read-only sports data API.

Resources