Record and track an individual API call with metadata
| Name | Required | Description | Default |
|---|---|---|---|
| method | Yes | HTTP method (GET, POST, etc.) | |
| endpoint | Yes | API endpoint URL | |
| duration_ms | Yes | Call duration in milliseconds | |
| status_code | Yes | HTTP status code | |
| service_name | No | Source service identifier | |
| response_size_bytes | No | Response payload size |
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 available, the description carries the full burden of behavioral disclosure. It only hints at a write/recording operation but does not explain side effects, persistence, authentication, or return values. This is insufficient for an agent to predict the tool's impact.
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, direct sentence with no filler. However, it is under-specified, which detracts from its structure since it omits valuable context; for a tool with 6 parameters, a slightly more detailed description would be appropriate.
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?
There is no output schema and no annotations, yet the tool has six parameters. The description is extremely brief and does not explain return values, the relationship to siblings, or any behavioral nuances. This leaves the tool largely underdocumented.
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 provides complete descriptions for all six parameters, so the baseline is 3. The description's mention of 'metadata' adds no specific meaning beyond the schema, so no additional credit is warranted.
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 records and tracks an individual API call with metadata, using specific verbs and a clear resource. This distinguishes it from the sibling analysis tools (analyze_flow, calculate_savings, etc.) which operate on flows or multiple calls.
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?
No guidance is provided on when to use this tool versus the sibling tools. The description does not mention any preconditions, alternatives, or exclusions, leaving the agent to infer usage from purpose alone.
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.
Each tool targets a distinct aspect of API flow analysis: overall flow, savings, redundancy, dependency graph, batching, and individual call tracking. No two tools have overlapping purposes.
All tool names follow a consistent verb_noun pattern using snake_case, making the set predictable and easy to navigate.
Six tools is well-scoped for an API flow analyzer, covering core diagnostics without unnecessary bloat or missing essentials.
The surface covers tracking, analysis, redundancy detection, batching, dependency graphing, and savings calculation. Minor gaps like cleanup or export are absent but not critical for the domain.