get_leaderboard
Get the agent leaderboard — top endorsed agents with reputation scores, newest agents, and category breakdown.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Get the agent leaderboard — top endorsed agents with reputation scores, newest agents, and category breakdown.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the content returned (endorsed agents, reputation scores, newest agents, categories), which is useful behavioral context. However, it does not mention whether the operation is read-only (implicit but not stated), pagination, sorting details, or any rate limits or permissions. The description adds some value but lacks depth.
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?
The description is a single, front-loaded sentence that efficiently conveys the tool's purpose and output components. Every phrase adds value without redundancy, making it highly concise and well-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?
For a no-parameter, no-output-schema tool, the description covers the key output sections: top endorsed agents, reputation scores, newest agents, and category breakdown. It lacks explicit mention of ordering or pagination, but given the simple nature of the tool, it is reasonably complete. Slightly more detail would make it fully comprehensive.
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?
The tool has zero parameters, so the schema provides no parameter details. The baseline for 0 parameters is 4, and the description does not need to add parameter semantics. It describes the output content, which is sufficient.
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?
The description clearly states the tool retrieves an agent leaderboard, and enumerates its contents: top endorsed agents with reputation scores, newest agents, and category breakdown. This explicitly differentiates it from siblings like get_trending or browse_agents, which serve different purposes.
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?
Usage is implied: use this when you want the leaderboard. However, the description does not explicitly state when to prefer this over sibling tools like get_trending or browse_agents, nor does it mention any exclusions or alternatives. It provides clear context but no explicit guidance.
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.
Several tools overlap in purpose, such as bridge_erc8004_lookup and bridge_erc8004_trust_check, trust_check, get_agent, and get_agent_reputation all returning trust or reputation data. Descriptions help clarify the distinctions, but the similarities could lead an agent to select the wrong tool.
Naming uses a mix of conventions: verb-noun (get_agent, search_agents), noun-first (compliance_report, dns_discovery), and prefix-based groupings (trust_*, bridge_*). While snake_case is consistent, the inconsistent verb/noun ordering and synonyms (lookup, check, verify) make it less predictable.
With 19 tools, the set is slightly heavy but still justified by the platform's broad feature set covering trust checks, reputation, teams, wishes, compliance, and credentials. Some tools could be merged (e.g., bridge_erc8004_lookup and bridge_erc8004_trust_check), but the count is not excessive for the apparent scope.
The tool surface focuses heavily on reading and checking trust data, but lacks obvious lifecycle operations such as updating or deleting agents, creating wishes, or managing endorsements. The presence of create_team without corresponding team management (update/delete) leaves a notable gap.