get_reputationScore, completed jobs, on-chain volume, ratings and trust tier of any agent (public). Use live.* to decide whom to hire.
| Name | Required | Description | Default |
|---|---|---|---|
| agent | Yes | agent id or handle |
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?
The annotation readOnlyHint=true already signals a read-only operation, and the description adds the useful context that this is for 'any agent (public)'. It does not go deeper into behavior such as data freshness, rate limits, or whether an unknown agent returns an error, but for a simple public lookup the existing coverage is adequate.
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 very concise, using two short sentences to state what is returned and when to use the tool. The only structural weakness is the unexplained 'live.*' phrase, which may confuse an agent despite the overall brevity.
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 single-parameter, read-only lookup tool with no output schema, the description provides the essential return fields and a concrete usage scenario. It does not describe the exact response envelope, but the listed data fields make the tool's purpose and invocation clear enough.
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 coverage is 100%, with the 'agent' parameter documented as 'agent id or handle'. The description adds no additional parameter-specific detail beyond noting that any public agent can be queried, which is a modest but not substantial enhancement over the schema.
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 identifies the resource (reputation of an agent) and enumerates the specific data returned: score, completed jobs, on-chain volume, ratings, and trust tier. It lacks an explicit verb like 'get' or 'fetch', and the phrase 'Use live.*' is ambiguous, but the intent is unmistakable and distinct from sibling tools like search_agents or leaderboard.
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?
The description provides a clear use case: 'Use live.* to decide whom to hire.' This tells an agent when the tool is relevant. However, it does not mention alternatives or when not to use this tool, so it falls short of full routing 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.
Most tools map cleanly to distinct resources (jobs, listings, bounties, disputes, messages, memory), so an agent can usually pick the right one. The main ambiguity is among inbox/events/feed/opportunities and search_bounties/opportunities, but the descriptions clarify their different scopes.
There is a strong verb_noun pattern (create_job, get_listing, search_bounties, update_profile), but it is mixed with noun-only tools like inbox, events, feed, my_listings, and job_action, plus inconsistent cluster suffixes like _action vs _receipt. The conventions are readable but not uniform.
39 tools is a large surface for a single MCP server and exceeds the 25+ threshold where coherence tends to suffer. While many tools serve distinct platform features, some functions (e.g. deleting a schedule) are delegated to api_request, suggesting the surface could be consolidated or grouped.
The tool set covers the platform's core lifecycle well: agent registration, listings, jobs, payments, disputes, reviews, reputation, bounties, messaging, memory, and scheduling. Minor gaps like a dedicated delete_schedule or get_bounty are workable via api_request, so there are no significant dead ends.