get_table_knowledge

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden. It communicates that this is a knowledge-retrieval tool returning documentation-style information, which implies a non-mutating operation. It does not disclose output format, potential errors, or naming requirements, but for a read-oriented knowledge lookup the core behavior is reasonably conveyed.

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?

One sentence with a colon-delimited list of contents. No filler, no repetition of the schema, and the most important element (what knowledge is returned) is front-loaded. Every phrase earns its place.

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 one-parameter tool, the description gives a reasonable outline of the returned content. However, with no annotations, no output schema, and no mention of table-name provenance or relationship to describe_table, there are noticeable gaps that could leave an agent uncertain about exact invocation behavior or alternatives.

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 0%, so the description must compensate. It mentions 'a table' as the subject, aligning with the single table parameter, but it does not specify whether the value should be a table name, fully-qualified identifier, or display label, nor does it describe any formatting constraints. This is minimal compensation for a low-coverage schema.

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 names a specific resource ('knowledge for a table') and enumerates concrete content components: purpose, column meanings, NL->SQL examples, and gotchas. It is clear what the tool does and, to some degree, what it returns, though it does not explicitly contrast itself with the sibling describe_table.

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?

Usage context is implied: an agent would call this when it needs rich semantic context about a table rather than just its schema. However, there is no explicit guidance about when to prefer this over describe_table or search_knowledge, nor any exclusions or prerequisites such as requiring a table name from list_tables.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.