search_query
Semantic-search a collection you indexed earlier; returns top-k matches with scores. Paid (~$0.0003 in KAS).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | ||
| top_k | No | ||
| collection | Yes |
Semantic-search a collection you indexed earlier; returns top-k matches with scores. Paid (~$0.0003 in KAS).
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | ||
| top_k | No | ||
| collection | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description carries full burden. Mentions cost and output format, but does not disclose auth needs, rate limits, or side effects. Semantic search is read-only, but this is implied, not explicit.
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?
Two concise sentences, front-loaded with purpose and output, then cost. No unnecessary 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?
For a simple search tool with no output schema, it covers purpose, prerequisite, cost, and output type. Lacks parameter details, but schema provides types. Adequate for agent understanding.
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 coverage is 0%. Description explains 'collection' (indexed collection) and 'top_k' (top-k matches), but 'q' (query) is not described. Partially compensates for two of three parameters.
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 performs semantic search on a previously indexed collection and returns top-k matches with scores. This distinguishes it from siblings like search_index (indexing) and registry_search.
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?
Indicates prerequisite (indexed collection) and cost (~$0.0003 KAS), implying when to use. Does not explicitly state when not to use or list alternatives, but context is sufficient.
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, with detailed descriptions that prevent ambiguity. Even within related domains (e.g., covenant operations, proving steps), the functions are well-separated and described.
Most tools follow a verb_noun or noun_noun pattern with underscores, but there are some single-verb names like 'catalog' and 'classify'. Within subdomains naming is consistent (e.g., kaspa_*, covenant_*, prove_*). Minor deviations prevent a perfect score.
36 tools is on the high side for a typical MCP server, but the broad scope (blockchain, payments, ZK proving, text processing, search, registry) justifies the count. It borders on being too large for easy navigation but remains reasonable.
The server covers a wide range of functionalities with no critical gaps for its stated domain. Minor gaps exist (e.g., no direct Kaspa send transaction tool), but the covenant tools provide a workaround. Overall, the surface is fairly complete.