Get a canonical, reproducible citation for a knowledge entry by id (title, domain, source, content_hash, kb_snapshot). Cite a fact so it can be re-verified later with coldstate_verify.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Stable knowledge entry id |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is clear. The description adds useful context by stating the citation is 'canonical, reproducible' and listing its fields, aligning with the idempotency hint and revealing what the output will contain.
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, with the core action in the first sentence and the purpose/cross-reference in the second. It is front-loaded, free of filler, and every phrase contributes to understanding.
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 parameter, complete annotations, and no output schema, the description sufficiently covers what the tool does and what the citation includes (title, domain, source, content_hash, kb_snapshot). It could go deeper into return format, but for this simple tool it is adequately 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?
The input schema fully documents the single 'id' parameter with description, minLength, and maxLength. The tool description only repeats that the operation is 'by id' without adding further constraints or formatting details, which matches the baseline of 3 for high schema coverage.
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 starts with a specific verb and resource: 'Get a canonical, reproducible citation for a knowledge entry by id.' It also enumerates the citation's components (title, domain, source, content_hash, kb_snapshot), which distinguishes it from sibling tools like coldstate_verify or coldstate_fetch.
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 second sentence, 'Cite a fact so it can be re-verified later with coldstate_verify,' provides a clear use case and explicitly ties the tool to a sibling for verification. While it doesn't list when not to use it, the context strongly implies the appropriate scenario.
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.