parse_get_brandFetch a concise public marketing brief for one brand, including Parse score, strengths, weak spots, top prompts, citation sources, related brands, and next research questions.
| Name | Required | Description | Default |
|---|---|---|---|
| slug_or_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, which is consistent. The description adds context that the response is 'concise' and 'public', and lists expected fields. However, it does not disclose additional behavioral aspects like response format, pagination, or authentication requirements beyond 'public'. With annotations present, the added value is moderate but not rich.
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, well-structured sentence that front-loads the action and resource. It is concise and every phrase adds value by listing the brief's contents, avoiding any fluff 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?
With one parameter and no output schema, the description covers the return contents in reasonable detail (list of fields). It lacks explicit guidance on input format and alternative usage scenarios, but for a simple tool the description is largely complete. The absence of output schema is mitigated by the content list.
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%, and the only parameter 'slug_or_id' has no description in the schema. The tool description does not explain the parameter format or acceptable values, relying solely on the self-explanatory name. This is insufficient for low coverage; the description should compensate by explaining that the slug or ID identifies the brand.
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 action ('Fetch') and resource ('a concise public marketing brief for one brand'). It lists specific content areas (Parse score, strengths, weak spots, etc.), making its purpose distinct from siblings like parse_get_stats and parse_get_prompt.
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 implies usage: when you need a public brief for a single brand. It does not explicitly exclude alternatives or state when not to use, but the clear scope ('for one brand') and distinct content provide enough context. Sibling names suggest other specialized tools, though no direct comparison is made.
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.
Most tools have distinct purposes: parse_get_brand fetches brand briefs, parse_get_prompt fetches prompts by slug, parse_get_stats explains the index, and parse_search does searching. However, the 'fetch' alias overlaps with parse_get_brand and parse_get_prompt by resolving IDs, causing potential ambiguity.
The four parse_* tools consistently follow a verb_noun pattern (parse_get_*). However, the two compatibility aliases 'fetch' and 'search' break this pattern, introducing minor inconsistency.
Six tools is a well-scoped set for a read-only research server focused on parsing and searching. Each tool serves a clear purpose without unnecessary bloat.
The server covers core read operations: searching, getting brand details, getting prompt details, and retrieving index statistics. Minor gaps exist (e.g., no direct tool for listing all brands or prompts), but the search tool handles discovery.