Cito API

by com.citoapi.api

list_capabilities

Read-only

Curated catalog of cito-mcp tools, games, jobs, and builder recipes.

When to use:

Session start or "what can you do?"
Mapping app screens to tools
Filtering by game or job (live_board, match_page, team_page, player_form, standings, h2h, schedule, preview, event_card, app_scaffold)

Prefer over: guessing from memory; exploring raw OpenAPI via call_api.

Do not use when: you already know the tool and have IDs — call that tool directly.

Parallel-safe: yes. Upstream cost: 0. Example: { "game": "cs2", "job": "live_board", "includeExamples": true }

Input Schema

TableJSON Schema

Name	Required	Description
`q`	No	Free-text filter over tool names and outcomes.
`job`	No	Filter by agent/builder job. Example: "team_page".
`game`	No	Filter catalog to one primary game; omit for all.
`includeRecipes`	No	Include multi-step recipes.
`includeExamples`	No	Include exampleArgs on each tool.

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

TDQS

A4.7/5.0

Behavior4/5

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

Annotations already cover readOnlyHint, openWorldHint, and destructiveHint. The description adds useful behavioral context: the result is a curated catalog (not a raw API dump), it is parallel-safe, and it has zero upstream cost. This goes beyond the structured annotations without contradicting them.

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 scannable and front-loads the purpose. Every section earns its place: use cases, exclusions, parallel-safety, upstream cost, and a concrete example. No fluff or repetition.

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?

The description fully covers when to use, when not to use, safety behavior, upstream cost, and gives an example call. With an output schema present, the agent has everything it needs to decide whether and how to invoke this tool.

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?

The input schema has 100% coverage with descriptions for each parameter, so the baseline is 3. The description adds an example payload and a shorthand list of job filters, which clarifies how to combine game/job/includeExamples in practice.

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 sentence defines the resource: the curated catalog of cito-mcp tools, games, jobs, and builder recipes. It is clearly distinct from data-lookup siblings like live_matches or match_details, and it explicitly contrasts itself with call_api for discovery use.

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?

Provides explicit 'When to use', 'Prefer over', and 'Do not use when' sections. This gives an agent concrete routing rules, including the exclusion case where direct tool calls should win.

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

All Cito API tools Inspect

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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

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