a9n9_research_statusReturn milestone progress and the final result for an opaque tracker code.
| Name | Required | Description | Default |
|---|---|---|---|
| trackerCode | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| error | No | ||
| result | No | ||
| status | Yes | ||
| quoteId | No | ||
| createdAt | No | ||
| statusUrl | No | ||
| trackerCode | Yes | ||
| progressStage | Yes | ||
| progressPercent | Yes | ||
| requestBodyHash | No |
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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds context about returning 'milestone progress' (indicating work in progress) and 'final result,' which is useful. However, it does not disclose behavior for invalid tracker codes, rate limits, or authentication requirements, which would be valuable.
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 sentence, front-loaded with the verb 'return' and the resource. Every word is necessary; there is no redundancy or fluff. It is optimally concise.
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?
Given the tool's simplicity (one parameter, output schema exists), the description covers the basic return content. However, it lacks usage context (when to call, prerequisites) and does not explain edge cases like pending results or errors. The output schema is present, so return structure details are not required, but the description is still incomplete for a new user.
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 0%—no description for the trackerCode parameter. The description's phrase 'opaque tracker code' provides minimal semantics (it's a non-human-readable identifier) but does not explain how to obtain it or its format beyond the pattern. This is insufficient to fully compensate for the lack of parameter documentation.
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 returns 'milestone progress and the final result for an opaque tracker code.' The verb 'return' and resource are specific, and the purpose is distinct from siblings like a9n9_research_start (starts research) and a9n9_research_submit_payment (payment).
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 no explicit guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as needing a tracker code from a9n9_research_start, nor does it exclude misuse (e.g., before research is started). Usage is only implied by the tool name and sibling 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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Each tool serves a distinct purpose: free search, quote generation, paid research initiation, status tracking, and payment submission. No two tools overlap in functionality, and descriptions clearly differentiate their roles.
All tools share the 'a9n9_' prefix and use snake_case. However, the pattern varies slightly: 'quick_search' uses adjective_noun, while others mix noun_noun and verb_noun constructions. The inconsistency is minor and does not hinder readability.
Five tools cover the essential stages of the research service (free search, quoting, payment, start, status) without unnecessary redundancy. The count is well-scoped for the domain.
The tool set covers the main workflow end-to-end. A minor gap is the lack of a tool to list or cancel past research jobs, but the core lifecycle (quote, pay, start, status) is fully represented.