list_agents
List your AI agents: id, name, mode, scenario, status, last decision/trigger.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
CoinCryptoRank MCP
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
B3.1/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not state whether the operation is read-only, safe, or has any side effects. The minimal description assumes safety but does not disclose it.
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 a single, focused sentence that immediately states the purpose and lists the output fields. It avoids fluff and is optimally concise with clear structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description identifies the output fields but does not specify the response format (e.g., list of objects), pagination, filtering, or whether all agents are always returned. It is adequate for basic use but leaves room for ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero parameters, so parameter description coverage is trivially 100%. The description adds no extra meaning because there are no parameters to elaborate on, resulting in a baseline score of 3.
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 states the verb 'List' and the resource 'your AI agents', enumerating the returned fields. It is distinct from other agent-related tools but does not explicitly contrast with siblings like get_agent_events or agent_chat, so it misses a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, no conditions or exclusions, and no mention of typical use cases. It simply states what it does without context.
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
B3.2/5.0
Disambiguation3/5
Many tools serve distinct purposes (hedging, funding, agents, market data), but several overlap heavily: get_basis_regime, get_basis_signal, get_basis_history, analyze_pair_liquidity, and get_perp_arbitrage all analyze exchange spreads/basis with blurred boundaries. Similarly, close_hedged_position vs close_position and hedge_status vs list_hedge_positions vs get_positions could cause misselection without careful reading.
Naming Consistency4/5
The set predominantly follows a verb_noun pattern (get_*, open_*, close_*, set_*, list_*, place_*) which is predictable and readable. Minor deviations exist: agent_chat, agent_trigger, and square_post break the convention, and the hedge-specific tools mix status/list/adjust naming inconsistently.
Tool Count3/5
35 tools is on the heavy side and pushes past the ideal scope for a single server. Many tools are data-retrieval variants (basis history/regime/signal/liquidity) that could be consolidated, and the breadth from news to square posts to agent management makes the surface feel sprawling rather than focused.
Completeness3/5
Core workflows (hedging, basis analysis, funding arbitrage, agent interaction, position management) are well covered, but there are noticeable gaps: there is no cancel_order tool despite get_open_orders and place_order existing, no order history or trade history, and no exchange-side position listing for real user positions. The server covers its niche but leaves some common trading dead ends.