run_volume_profile_poc_reversion_study

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

With no annotations provided, the description carries the burden of behavioral disclosure. It states the study is descriptive only, never ranks or adopts a branch, is separately frozen, and uses an exact audited proxy. It does not disclose operational side effects such as history loading, resource usage, or whether prior chart state is touched, but the core non-mutating, non-decision-making behavior is clear.

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 three sentences with no filler. It front-loads the tool's core purpose, then defines the signal and measurements, and ends with the key exclusions. Every sentence contributes distinct information.

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 definition is conceptually rich and clarifies what the study measures, which is helpful since there is no output schema. However, for a 10-parameter tool with no annotations and very low schema coverage, it lacks operational guidance on required identifiers, fold definitions, signal windows, and event limits. An agent could select the tool correctly but would still struggle to fill several parameters correctly without external knowledge.

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 only 10%, so the description should compensate for the ten parameters. It does not explain required fields like pine_id, study_id, expected_symbol, expected_timeframe, nor optional controls like folds, signal_from, signal_to, or event_limit. The description adds useful conceptual context about the signal and measurements, but it does not help an agent map concepts to specific parameters.

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 the exact study to run (the separately frozen descriptive #61b 60-minute POC-reversion study), the data scope (CME exchange-volume chart bars and the audited Bushido Volume Profile Context proxy), and the signal definition. It also explicitly distinguishes itself from the VAH/VAL reaction study, so a reader can identify its unique purpose.

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 clearly states a when-not condition: it is not the VAH/VAL reaction study and its evidence must not be combined with that population. It also says it is descriptive only and never ranks or adopts a branch, which prevents misuse for decision-making. However, it does not explicitly name a positive alternative tool or give a precise selection rule among the many study siblings.

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