to_tf_template

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

With no annotations, the description carries full burden. It discloses determinism, no model involvement, transformation rules (brackets to indentation, AND to space, quoted strings lose quotes), and handling of GET clauses and refused operators. More detail on error handling could improve it.

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 (4 sentences), front-loaded with the core purpose, and each sentence adds unique value. No wasted words.

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?

The description covers purpose, behavior, limitations, and sibling relationship. For a conversion tool with one parameter and no output schema, it is largely complete. Could mention output format explicitly.

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 description adds meaning to the single parameter 'mql' by specifying it is an 'Emdros MQL query', but does not elaborate on expected format or syntax. Given 0% schema coverage, this provides necessary context but could be more precise.

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's purpose: converting an Emdros MQL query to a Text-Fabric search template. It also differentiates from siblings by noting it is the mirror of to_citable_mql, and its behavior contrasts with run_mql and run_tf.

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 implies when to use (for conversion) and specifies limitations (refuses OR, NOT, FOCUS, sequence operators). However, it does not explicitly state when not to use or provide alternatives among siblings.

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