Resolve a partial or misspelled server name to its EXACT registry id before calling should_i_use / check_server. Matches a fragment against registry NAMES only (not capabilities — for 'which tool does X' use find_tools). Returns candidate exact names with each one's latest liveness outcome. Empty query rejected.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | a fragment of a registry name, e.g. 'tariff' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that matching is against registry names only, returns candidate names with liveness outcomes, and rejects empty queries. It does not explicitly state read-only status or behavior on no matches, but the phrasing implies a read-only resolution operation, making it fairly transparent.
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 three sentences with no wasted words. The first sentence states the purpose and usage context, the second clarifies the scope and alternatives, and the third states the return value and rejection behavior. Every sentence earns its place.
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 is simple (one parameter, no output schema), and the description provides all necessary context: what it does, when to use it, what it returns, and an edge-case behavior (empty query rejected). It fully compensates for the lack of an output schema by describing the return format meaningfully.
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 100% for the single 'query' parameter, which is described as 'a fragment of a registry name'. The tool description adds context beyond the schema by clarifying that the query is matched against registry NAMES only (not capabilities), reinforcing the fragment semantics. This adds meaningful value over the schema alone.
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: resolving a partial or misspelled server name to its exact registry ID. It specifies the verb 'Resolve', the resource (server name), and the output (exact registry id), while also distinguishing itself from sibling tools like find_tools by noting it matches against names only, not capabilities.
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?
Explicitly instructs to use this tool before calling should_i_use / check_server, and provides an explicit alternative for capability-based queries ('for "which tool does X" use find_tools'). This gives clear when-to-use and when-not-to-use 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 has a clearly distinct purpose: should_i_use gives a quick verdict, check_server provides full evidence, find_tools searches by need, resolve_server_name handles name resolution, registry_pulse is a snapshot, changes_since is a diff, report_call sends feedback, and list_findings lists established findings. No two tools are easily confused.
Most tools follow a verb_noun pattern (check_server, find_tools, list_findings, report_call, resolve_server_name), but 'changes_since' and 'should_i_use' deviate, and 'registry_pulse' is noun_noun. The mixed conventions are still readable and predictable overall, but not perfectly uniform.
Eight tools is a well-scoped number for an observatory server. Each tool covers a distinct aspect of the lifecycle: discovery, decision, investigation, reporting, and ecosystem awareness. No tool feels redundant or missing.
The tool surface fully covers the verifier's domain: get a verdict (should_i_use), deep evidence (check_server), search by need (find_tools), resolve fuzzly names (resolve_server_name), ecosystem stats (registry_pulse), changes over time (changes_since), user feedback (report_call), and public findings (list_findings). There are no obvious gaps in the workflow.