This is a duplicate of the actual entry deprecating this in favor of the original.
Tell one approval request's story from its audit events: the pipeline's conclusion and the block that asked for a person, every AI judge assessment, the escalation steps and the claim history. Needs only request.read on the request, not audit.read.
| Name | Required | Description | Default |
|---|---|---|---|
| request_id | Yes | The approval request's id, for example an audit event's subject_id when subject_type is approval_request. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds genuinely new behavioral context: an unexpected permission requirement (request.read rather than audit.read) and a preview of the composite content returned. It does not cover pagination or ordering, which keeps it from a 5.
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?
One dense sentence that front-loads the core action and closes with the permission detail. Slight flourish in 'tell one approval request's story,' but no wasted sentences.
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?
With no output schema, the description carries the burden of describing returns, and it does list the timeline's components plus the auth requirement. Ordering, pagination, and error behavior are unaddressed, leaving a small gap.
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 description coverage is 100% and the single request_id parameter is already documented in the schema with a concrete example (an audit event's subject_id). The description adds no additional parameter meaning, so the baseline of 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?
States a specific verb and resource — assembling one approval request's timeline from its audit events — and enumerates what the timeline contains (pipeline conclusion, human-approval block, AI judge assessments, escalation steps, claim history). This clearly distinguishes it from the raw event retrieval siblings like get_audit_event and list_audit_events.
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?
Explicitly states the authorization context: 'Needs only request.read on the request, not audit.read,' which implicitly tells an agent it can use this instead of audit-scoped tooling. It stops short of naming a specific alternative tool or a when-not-to-use condition, so it is clear but not fully routing.
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.