list_agentsVALORANT reference data (valorant-api.com) — list playable agents with their roles and abilities. Static game data, keyless. Optionally filter by role.
| Name | Required | Description | Default |
|---|---|---|---|
| role | No | Optional role filter (case-insensitive), e.g. "Duelist", "Controller", "Initiator", "Sentinel". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate safe read operation. Description adds key details: static game data, keyless access, and role filter option. 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no redundant words, effectively structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers the essential purpose and filter option. Lacks details on output format, but given no output schema and simple list, it's sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has full description for the single parameter. Description adds minimal new info beyond repeating 'optionally filter by role'. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it lists playable agents from VALORANT API, including roles and abilities. Differentiates from siblings like get_agent and list_maps.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context about static, keyless data and optional role filter. Implies use for retrieving all agents, but does not explicitly compare with get_agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.