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bsee_hpht_regulatory_classifier

Classifies Gulf of Mexico deepwater wells under BSEE NTL 2019-G03 and API 17TR8 to determine if 20,000 PSI Tier-1 rules, I3P verification, or CVA approval apply.

Instructions

Classifies Gulf of Mexico deepwater wells under BSEE NTL 2019-G03 and API 17TR8 guidelines, determining whether 20,000 PSI Tier-1 regulations, Independent Third-Party (I3P) verification, and Certified Verification Agent (CVA) approvals are legally triggered.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
water_depth_ftNoWater depth in feet. Default: 6000.0 ft.
bottomhole_temperature_fNoBottomhole temperature in degrees Fahrenheit. Default: 250.0°F.
shut_in_tubing_pressure_psiYesShut-in tubing pressure (SITP) in PSI (e.g. 12000, 16500, 19500).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the regulatory framework and the nature of the determination, which is useful context, but it does not state whether the tool is read-only, deterministic, whether it requires authoritative inputs, or whether there are side effects or rate limits.

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 a single, information-dense sentence with no wasted words. It is front-loaded with the core verb and scoped resource, and every clause contributes to purpose or regulatory trigger detail.

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

Completeness3/5

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

Given the regulatory complexity, the absence of an output schema, and no annotations, the description is only partially complete. It indicates the determination outcomes but omits return format, usage conditions, and behavioral constraints, leaving some gaps for an agent to infer.

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 100%, so all three parameters are already documented in the input schema. The description does not add parameter-specific syntax, constraints, or examples beyond what the schema provides, making 3 the appropriate baseline for high schema coverage.

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

Purpose4/5

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

The description names a specific verb ('Classifies'), resource ('Gulf of Mexico deepwater wells'), regulatory standards, and the exact regulatory triggers it determines. It is not a tautology and is very clear, but it does not explicitly distinguish itself from sibling tools such as lookup_gom_protraction_area or estimate_tieback_economics.

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

Usage Guidelines2/5

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

The description explains what the tool determines but gives no when-to-use guidance, no prerequisites, no exclusions, and no mention of alternatives. Usage must be inferred from the regulatory context rather than stated directly.

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