Verify-before-mark: checks that the expected schema is actually present
in the live DOM of the site before marking the quick win as applied.
Only marks it if the expected @type is found among the schemas detected
on the domain (best-effort, fails safe).
Requires a valid API key.
| Name | Required | Description | Default |
|---|---|---|---|
| hash | Yes | ||
| domain | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses authentication requirements (valid API key), the verification logic, and the fail-safe behavior ('best-effort, fails safe'), which are not present in the annotations. This adds valuable context beyond readOnlyHint=false.
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?
Three sentences, front-loaded with the core behavior. No wasted words.
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 has only 2 params and no output schema, the description covers the primary behavior, prerequisites, and failure modes. It lacks explicit parameter definitions, but overall it's adequate for an agent to understand the tool's operation.
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 has no descriptions and the description doesn't explain the 'hash' parameter or the 'domain' parameter beyond implying the domain is where the schema is checked. Since schema coverage is 0%, the description should compensate but doesn't.
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 purpose: marking a quick win as applied, with a verification step. It distinguishes from sibling verify_installation by emphasizing it actually marks the quick win (the 'mark' verb) and does so conditionally based on DOM schema presence.
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?
Provides clear context that this tool should be used when you want to mark a quick win as applied only after verifying the expected schema is present in the live DOM. However, it doesn't explicitly name alternatives or exclusions, so it stops 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.
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.