Search Nstok-db schemas by name, table, or field to retrieve entity definitions for models like Product, Inventory, and User.
Search database schemas and entity definitions in Nstok-db (Product, Inventory, Sale, User, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Search database entities by name, table name, or field name (e.g. "Product", "inventories", "sku") |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It never states that this is a read-only operation, nor does it describe result format, matching behavior (partial vs exact), result limits, or pagination. For a search tool with zero annotation coverage, that is a meaningful gap.
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?
A single efficient sentence with the resource and scope front-loaded and no filler. It is arguably terse for the amount of differentiation the agent needs, but nothing is wasted.
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 optional parameter, no output schema, and no annotations, the description is minimally sufficient but leaves the agent guessing about return shape and how results differ from the other find_*/search_* tools. Adequate as a search stub, not 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 100% with a single optional query parameter, so the schema already documents name/table/field matching and gives examples. The description adds the domain (Product, Inventory, Sale, User) but no syntax or matching detail beyond the schema, so the baseline 3 applies.
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?
States a specific verb (search) and resource (database schemas and entity definitions) scoped to the named Nstok-db system, with concrete examples (Product, Inventory, Sale, User). It does not, however, distinguish itself from sibling lookups like search_knowledge or find_existing_patterns, so an agent must infer the boundary.
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?
There is no explicit when-to-use or when-not-to-use guidance and no named alternative among the many find_* and search_* siblings. The agent must infer from the word 'search' alone that this targets schema/entity metadata rather than code, UI, or knowledge.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.