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append_queries

Combine rows from multiple queries into one table by appending them (union operation). Use this to stack data from other tables onto your current query.

Instructions

Power Query Append: stack the rows of one or more other queries onto this table (union). Appends Table.Combine to the table's M query. otherTables is comma-separated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYes
sessionIdYes
otherTablesYesqueries/tables to append, comma-separated
partitionNameNopartition name (optional; defaults to the first partition)
Behavior3/5

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

With no annotations provided, the description carries the full burden. It does disclose that the tool appends Table.Combine to the table's M query, revealing a side effect on the query definition. However, it does not mention whether the operation is reversible, requires specific permissions, or how it affects existing data, which is a gap for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three concise sentences, front-loaded with the core action ('Power Query Append: stack the rows...'). Every sentence provides useful information without redundancy, achieving high information density.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 4 parameters and no output schema, the description covers the main behavior, the implementation detail (Table.Combine), and a critical parameter format (comma-separated). It is fairly complete for a table mutation operation, though it omits details about return values and prerequisites, which are not critical for basic use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50%, and the description adds clarity by noting that otherTables is comma-separated, which directly aids invocation. However, it does not explain the 'table' parameter beyond referring to 'this table', and sessionId remains undocumented. While the description partially compensates, it does not fully clarify all parameter meanings.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool appends rows from one or more other queries onto the target table via a union operation, explicitly mentioning 'stack the rows' and 'union'. This is a specific verb+resource pairing that distinguishes it from sibling tools like merge_queries.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the use case (appending/stacking rows) but does not explicitly state when to use this tool versus alternatives or provide exclusions. It lacks guidance on prerequisites or scenarios where append is inappropriate, making it only implicitly informative.

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

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