Get EU AI Act compliance report for an agent. Returns risk level, transparency declaration, audit summary, and trust status. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | Yes | Agent ID (e.g., agt_E-PFtTAIQlfVleNm) |
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 provided, the description carries the full burden. It discloses the main behavioral outcome (returns report with specified fields) and adds that it is free, which is useful. However, it does not mention any side effects, authorization requirements, or read-only status explicitly, though 'Get' implies a safe operation. This is adequate but not rich.
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 extremely concise—two short sentences that state purpose and a notable feature (free). No filler or redundancy.
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 tool with no output schema, the description adequately specifies the input and the output structure by listing the returned fields. It also gives a relevant qualifier ('Free'). It could be improved by noting if any prerequisites exist, but overall it is complete for this simple tool.
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 schema already documents agent_id with a descriptive placeholder and example (100% coverage). The description adds no further parameter-specific detail, so the baseline of 3 applies.
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 uses a specific verb 'Get' and names the exact resource 'EU AI Act compliance report' for a specific target 'an agent'. It also enumerates the key return fields (risk level, transparency declaration, audit summary, trust status), clearly differentiating it from sibling tools like trust_check or get_agent.
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 implies clear context: it is for retrieving an EU AI Act compliance report, which is distinct from trust checks or general agent lookups. However, it does not explicitly state when not to use it or mention alternatives, so it falls short of full 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.
