estimate_carry_panel_effective_sample

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

With no annotations provided, the description carries the full behavioral burden, and it discloses real methodology: 'resamples whole anchor-date cross-sections in circular moving blocks, preserving same-date pair dependence and serial dependence.' It also states its role boundary as a planning diagnostic rather than an adoption rule or return-study runner. It does not disclose output format or explicitly flag stochasticity (despite the required seed), which keeps it from a 5.

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?

Three sentences with zero waste: purpose, methodology, then role boundaries. Each sentence earns its place and the purpose is front-loaded. The statistical method disclosure is dense but compact.

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 what, how, and when well, but there is no output schema and no mention of return semantics — for a stochastic estimator the result shape (point estimate, distribution, confidence bound?) matters. It also leaves seed/iterations unexplained and does not state prerequisites or runtime characteristics. Solid on the conceptual side, incomplete on the invocation side.

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, and it partially does: 'circular moving blocks' hints at block_length_anchors and 'resamples' hints at the stochastic role of seed/iterations. However, no parameter is explicitly mapped or explained — seed, iterations, and observations receive no direct semantic treatment. The methodology language adds some meaning beyond the schema but does not fully cover the 4-parameter space.

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 verb and resource: 'Estimate the precision-equivalent sample size of an already fixed carry panel.' The timing qualifier 'before its primary test' and scope 'already fixed carry panel' sharply distinguish it from siblings like run_carry_core_primary_test (which runs the test) and measure_carry_panel_dependence (which measures dependence). No ambiguity about what this tool does.

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 gives clear when-to-use context ('before its primary test') and explicit when-not-to-use boundaries ('a planning diagnostic only, never an adoption rule or a return-study runner'). It does not name sibling alternatives by name, but the exclusions implicitly route the agent away from adoption and return-study tools. Missing only explicit alternative tool names for a 5.

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