Resolve a name, alias, or surface form to its canonical ColdState knowledge entry (id + title). Deterministic: an exact title match wins, else the top relevance-Ψ entry. Returns the canonical entry plus alternatives. Use the returned id with coldstate_fetch / coldstate_related.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max alternative candidates | |
| query | Yes | The name/term/alias to resolve |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (which already declare safe/idempotent read), the description adds deterministic matching behavior (exact title match wins, else top relevance-Ψ) and the output composition (canonical entry plus alternatives). This provides meaningful behavioral context beyond what structured fields convey.
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 (four sentences) and front-loaded with the core action, followed by deterministic behavior, output summary, and a follow-up tip. Every sentence contributes information without waste.
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?
Given the simple tool, complete schema, and safe annotations, the description adequately covers the return value (canonical entry + alternatives), deterministic behavior, and downstream usage. No output schema exists, so the description's explicit mention of id + title and alternatives suffices for an agent to invoke correctly.
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 has 100% coverage with descriptions for query and limit. The description minimally reinforces query's semantics but doesn't add details beyond the schema; the limit's effect on alternatives is implied but not explicitly explained in the description.
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 explicitly states the tool resolves a name/alias/surface form to a canonical ColdState entry with id + title, and distinguishes it from siblings by mentioning follow-up tools coldstate_fetch and coldstate_related. It uses a specific verb and resource, making its purpose unmistakable.
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 clearly implies the usage context: when you have a name/alias and need the canonical ID, and it directs to use the returned id with coldstate_fetch/coldstate_related. However, it doesn't explicitly contrast with sibling search tools or mention when not to use it, 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.