BEFORE building something, call this: returns the CURRENT (date-stamped), cited, tool-aware way to do a task, so you build from today's best practice instead of training-cutoff memory. Composes live web research + the tool resolver + one synthesis pass into { approach, recommendedTools, steps, gotchas, deprecated, sources, asOf }.
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the tool's behavior thoroughly: it composes live web research, the tool resolver, and a synthesis pass, and it enumerates the exact output structure ({ approach, recommendedTools, steps, gotchas, deprecated, sources, asOf }). This transparency exceeds typical descriptions and establishes clear expectations for the agent.
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 concise, with the key usage instruction ('BEFORE building something') front-loaded. It is split into two clear sentences and avoids unnecessary jargon or fluff. It could be slightly more streamlined, but it remains well-structured and scannable.
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 description covers the tool's core purpose, the high-level process, and the output format. For a single-parameter tool, it is fairly complete. Minor omissions include no mention of error handling or behavior on invalid input, but these are not critical for typical use.
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?
There is only one parameter, 'task', but the schema provides no description, and the tool description only refers to it as 'a task' without detailing type, format, or examples. Since schema coverage is 0%, the description fails to compensate by explaining the parameter's intended value, leaving the agent to infer its meaning.
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: to return the current, date-stamped, cited, tool-aware way to perform a task. It also provides the context (before building) and the rationale (to avoid training-cutoff memory). This is unambiguous and directly tells an agent what the tool is for.
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 explicitly instructs to call this tool 'BEFORE building something', giving a concrete trigger for usage. It also explains the benefit (using today's best practice). However, it does not mention any alternatives or conditions when not to use it, so it falls slightly short of fully covering usage guidelines.
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.
resolve and find_tools_for_task both return ranked tool recommendations for a task, and how_to also surfaces recommendedTools, making their boundaries unclear. search_tools adds further overlap as a registry search by query and requirements. The company/research and registry lookup tools are more distinct, but the task-to-tool cluster is genuinely confusing.
The naming is almost entirely snake_case verb_noun: get_company, find_competitors, search_tools, compare_products, list_registry. The exceptions are audit and resolve as bare verbs and how_to as an idiom, but they are still recognizable.
Fifteen tools is at the upper end of a reasonable range, and the broad scope of registry lookup, research, comparison, audit, and interface generation supports a larger surface. However, find_tools_for_task largely duplicates resolve, so the count is slightly higher than necessary.
The server covers the main registry lifecycle: listing, searching, getting records, comparing, researching, pricing, readiness auditing, and generating agent interfaces. It is intentionally read/research-oriented, so the lack of registry CRUD is not a severe gap. Minor missing pieces like direct per-product OpenAPI retrieval or registry entry management are workable around.