identification_analysis

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

With no annotations provided, the description carries the full burden. It discloses the core behavior (compares empirical ACF/PACF with theoretical, returns top-5 suggestions) and adds context like 'series is used, model spec ignored' and the internal call relationship with guided_identification. It does not explicitly state side effects, but for an analysis tool this is reasonably transparent.

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 well-structured with a clear main statement, a note block, and a parameter list. It is slightly verbose in the note section, but every part contributes useful information. The front-loaded purpose and usage guidance make it easy to scan.

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 tool's moderate complexity and absence of an output schema, the description is quite complete. It explains the input file handling, parameter meanings, the algorithm (comparison of ACF/PACF), and the return (top-5 suggestions). It could further detail the output format, but the core information for an agent to select and invoke the tool is present.

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 does so fully by explaining each parameter: inp_path, d (regular differencing), D (seasonal differencing), and lam (Box-Cox with 0=log, 1=identity), including defaults. This goes well beyond the bare schema and resolves potential ambiguity.

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 function: 'ACF/PACF identification listing + ARMA order suggestions'. It uses a specific verb ('compares', 'returns') and identifies the resource (differenced series). It also distinguishes itself from the sibling tool 'guided_identification' by explicitly marking this as standalone vs. guided use.

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 provides explicit when-to-use guidance: 'standalone use' and directs users to 'guided_identification' for guided analysis. It even outlines the specific call sequence for the guided alternative, giving clear context and exclusion criteria.

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