List Maps
list_mapsRead-onlyIdempotent
VALORANT reference data (valorant-api.com) — list maps with tactical description and icon. Static game data, keyless.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Valorant
TDQS
A4.5/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint false. The description adds value by specifying the data is static and keyless, reinforcing the read-only, safe behavior. No contradictions.
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?
Single sentence that front-loads the source and purpose, covering all essential information without fluff. Every word contributes value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no parameters and no output schema, the description adequately states what the tool returns (maps with tactical description and icon). However, it could be more explicit about the output structure (e.g., field names). Still, it is sufficient for an agent to understand the tool's purpose.
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?
Tool has zero parameters, so schema coverage is 100% by default. The description correctly implies no input is needed, which aligns with the empty schema. No additional parameter documentation is necessary.
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?
Description clearly specifies verb+resource: 'list maps' for VALORANT game data. It identifies the data source (valorant-api.com) and what it returns (tactical description, icon). This differentiates it from siblings like list_weapons which also deal with game data but a different resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Context is clear: it's for retrieving static VALORANT map data without authentication (keyless). While no explicit when-not-to-use or alternatives are given, the nature of the tool (read-only static data) and the sibling list show no direct overlap, making exclusions unnecessary.
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
A3.8/5.0
Disambiguation2/5
Multiple tools have unclear boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly described as currently identical, and ask_pipeworx_grounded shares the same router. ai_visibility_check is internally wrapped by scan_competitor_ai_presence, discover_tools and suggest_questions both claim 'use this FIRST' as onboarding meta-tools, and entity_profile/compare_entities/recent_changes pull overlapping EDGAR/news/patents data. The detailed descriptions help, but the redundancy is structural, not just cosmetic.
Naming Consistency3/5
All names are snake_case and several families are internally consistent (ask_pipeworx_*, polymarket_*, list_*), but the overall set mixes bare verbs (remember, recall, forget, subscribe), verb_noun (get_agent, compare_entities), noun_noun (entity_profile, bet_research, recent_changes), and adjective/compound forms (deep_research, generate_llms_txt, ai_visibility_check) with no dominant convention. Readable, but clearly heterogeneous.
Tool Count2/5
35 tools is above the 25+ 'too many' threshold, and the count is wildly mismatched to the server's stated identity: a server named 'Valorant' has only 4 game-related tools while the other 31 form a sprawling data-research/prediction-market/utility toolkit. Even considered on its own terms, the set includes several redundant meta-tools and unrelated subsystems (npm scanning, llms.txt generation, memory) that feel bolted on.
Completeness3/5
The dominant data-research domain is well covered: discovery, single and grounded queries, deep research, entity resolution, profiles, comparisons, change feeds, claim validation, and subscription monitoring form a mostly complete surface. However, the server's namesake domain is severely shallow — the Valorant tools only expose static reference data with no match/player/esports coverage — and the prediction-market side lacks obvious write-side or position-management operations.