Run several knowledge-base queries in one call against a single consistent kb_snapshot. Returns each query with its ranked results — efficient and snapshot-consistent across the whole batch.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results per query | |
| domain | No | Optional domain filter applied to all queries | |
| queries | Yes | 1–10 queries |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnly/idempotent annotations, the description adds meaningful context: it explains the snapshot-consistent behavior across the batch and that results are ranked per query. This is useful behavioral information not present in the annotations.
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 two sentences, front-loaded with the main action, and every clause adds value. It avoids fluff and clearly communicates the batch behavior and return format.
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?
It adequately describes the return shape ('ranked results per query') and the snapshot-consistency guarantee, which is sufficient given the simple 3-parameter schema and the safety annotations. No output schema exists, so the description covers the essential outcomes.
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?
The input schema already provides 100% coverage with descriptions for all three parameters (limit, domain, queries). The tool description does not add any parameter-specific semantics beyond the schema, so the baseline of 3 is appropriate.
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 runs multiple knowledge-base queries in one call against a consistent snapshot, and returns ranked results per query. This distinguishes it from single-query siblings like coldstate_search by emphasizing the batch aspect.
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?
It provides clear context: use when you want to run several queries efficiently with snapshot consistency. However, it does not explicitly name alternative tools (e.g., coldstate_search) or state when not to use this batch variant, so it stops short of full exclusion 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.
Most tools have clearly distinct purposes, but the three search tools (search, search_global, batch_search) and the two relation tools (related, isomorph) could cause initial confusion despite clear descriptions. Overall boundaries are clear enough that agents should select correctly with careful reading.
Every tool uses the consistent coldstate_ prefix followed by a descriptive verb_noun pattern (e.g., batch_search, browse_documents, list_indexes). The naming is uniform and predictable, making the toolset easy to navigate.
At 16 tools, the server sits at the upper edge of what feels reasonable, and the calibration guidance flags 16-25 as heavy. However, each tool serves a distinct function in the knowledge-search lifecycle, so the count is defensible but still slightly high for a single server.
The toolset covers the full read-only knowledge workflow: searching, browsing, fetching, citing, verifying, explaining, resolving, and exploring relations. It also includes meta-tools for capabilities, domains, snapshots, and statistics, leaving no obvious gaps for its stated purpose.