Return the traffic erosion model for the authenticated client:
cascading metrics with their *_source provenance labels, plus the
resulting revenue-at-risk calculation.
Use when an agent needs to assess the economic impact of losing
traffic to AI-generated answers.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, and the description adds behavioral context about what the return includes: 'cascading metrics with their *_source provenance labels, plus the resulting revenue-at-risk calculation.' Since annotations already cover the safety profile, the description's additional detail about output content earns a 4.
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 two sentences, front-loaded with the primary action and resource, then provides a concise usage guideline. Every word adds value, with no fluff or repetition of the tool name.
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 zero-parameter read-only tool with no output schema, the description fully covers what the tool does, what it returns, and when to use it. It also conveys authentication context ('authenticated client'), making it self-contained.
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 input schema has zero parameters, so schema coverage is 100% and the baseline is 4. The description does not need to explain parameters; it instead focuses on the tool's purpose and return value.
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's function: 'Return the traffic erosion model for the authenticated client' with specific details about cascading metrics and revenue-at-risk. This distinguishes it from sibling tools like get_artifact or get_bot_activity, which target different data.
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 an explicit use case: 'Use when an agent needs to assess the economic impact of losing traffic to AI-generated answers.' It gives clear context for when to invoke this tool, though it does not mention alternatives or when not to use it.
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 resource and action, though analyze_geo overlaps slightly with get_bleed_model and get_competitor_actions. Descriptions clarify the differences, making misselection unlikely.
All tools follow a consistent snake_case verb_noun pattern (activate_artifact, get_bot_activity, mark_applied). Minor deviations like analyze_geo instead of get_geo_analysis don't break the pattern.
16 tools is slightly above the typical 3-15 range, but the server covers multiple subdomains (artifacts, analysis, quick wins, reporting), so each tool has a clear purpose.
The tool set covers the full artifact lifecycle (generate, list, get, approve, activate, regenerate) and the core analysis metrics. Minor gaps like no explicit delete tool for artifacts exist, but regenerate serves that need.