Generate ready-to-install code for a quick win, identified by its hash.
Only available for structured_data quick wins.
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?
Annotations declare readOnlyHint=true, already establishing the read-only safety profile. The description adds valuable behavioral context beyond annotations: an API key is required and only structured_data quick wins are supported. These constraints are not present in the annotations and help set expectations, with no contradiction.
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 concise sentences, front-loading the core action ('Generate ready-to-install code') and quickly adding constraints. Every sentence carries useful information with no filler or redundancy.
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?
The tool has no output schema and 0% parameter coverage, so the description carries a heavier burden. It covers purpose, constraints, and authentication, but leaves the domain parameter's purpose and the expected output format unspecified. Given the tool's simplicity and existing annotations, it is adequate but not fully complete.
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%, so the description must compensate. It explains the hash parameter via 'identified by its hash', but the domain parameter is entirely unexplained. Since one of two parameters lacks any semantic context, the description only partially compensates for the missing schema descriptions.
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 generates ready-to-install code for a quick win identified by hash, specifying a concrete action and resource. It distinguishes itself from list-oriented siblings like get_quick_wins by focusing on code generation, but does not explicitly name alternatives. The structured_data constraint adds useful specificity.
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 a clear condition: only available for structured_data quick wins, and requires a valid API key. It implies the tool is used when you have a hash and need code, but it does not explicitly mention when to use alternatives like get_quick_wins or mark_applied. This gives clear context but lacks exclusions or alternative 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.