Cito API

resolve_entity

Read-only

Natural-language / fuzzy query → best typed entity ID(s) + game (player, team, event, tournament, match, fighter).

When to use:

User named an entity without an ID ("T1", "s1mple", "IEM Cologne", "Islam Makhachev")
Need a canonical id/slug before profile or match tools

Prefer over search_entities when you want one best match (or small ranked set) to chain. Prefer search_entities when browsing many results with pagination.

Do not use when: you already have a stable id/slug from a prior tool.

Empty/ambiguous results still return ok:true with best=null or needsDisambiguation=true — pick from candidates or refine q/game/type. Does not emit AMBIGUOUS_ENTITY as a hard error.

Parallel-safe: yes. Upstream cost: 1–5. Example: { "q": "T1", "game": "lol", "type": "team", "limit": 5 }

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "q": "<q>"
    },
    "name": "resolve_entity"
  }
}

Input Schema

Name	Required	Description	Default
`q`	Yes	Search text (name or tag). Keep short.
`game`	No	Strongly recommended. If omitted, fans out across primary games and ranks candidates.
`type`	No	Entity type bias. Example: "team".	any
`limit`	No	Max ranked candidates (default 5, max 10).

Output 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.

Changed1 schema field changedNov 14, 2026

changedInput schema / properties / game / enum

Previous value: -[
-  "lol",
-  "cs2",
-  "dota2",
-  "cod",
-  "ufc",
-  "tennis"
-]New value: +[
+  "lol",
+  "cs2",
+  "dota2",
+  "cod",
+  "ufc",
+  "tennis",
+  "valorant"
+]

First observedSep 1, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already declare readOnly/openWorld/non-destructive, but the description adds genuinely new behavior: empty and ambiguous results still return ok:true with best=null or needsDisambiguation=true, and no AMBIGUOUS_ENTITY hard error is emitted. It further discloses parallel-safety and rough upstream cost (1–5), which an agent needs for planning and retry logic.

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

Conciseness4/5

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

The purpose is front-loaded and the body is organized under clear headings (When to use / Prefer / Do not use / behavior / example), with no filler sentences. The opening line's arrow shorthand is slightly cryptic on first read, which keeps it just short of a 5.

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?

An output schema exists, so return shape needn't be restated, yet the description covers the non-obvious outcome states (null best, disambiguation flag) that the output schema does not signal as a decision point. Combined with cost, parallel-safety, and chaining guidance, nothing an agent needs to call this correctly is missing.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds meaning by tying parameters to the recovery flow — refine q/game/type when disambiguation is flagged — and shows an example payload combining q, game, type, and limit. That is incremental value over the schema rather than repetition.

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 first line states a specific transformation: fuzzy/natural-language query in, best typed entity ID plus game out, and enumerates the entity types it resolves (player, team, event, tournament, match, fighter). It explicitly contrasts itself with search_entities, so an agent can distinguish the two without opening either schema.

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 gives concrete when-to-use triggers with example inputs ("T1", "s1mple", "IEM Cologne"), states the prerequisite workflow (need canonical id/slug before profile or match tools), and names the alternative plus the condition that selects it (browsing/pagination → search_entities). It also gives an explicit exclusion: do not use when you already hold a stable id/slug.

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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