NatGasLens — US Natural Gas Data

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

No annotations provided, so the description carries full burden. It discloses return of honesty stats, disclaimer, and behavior of include_history parameter. It also mentions demo scope limitations, providing good transparency.

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 dense and informative but slightly verbose in the first sentence. It is well-structured with key information front-loaded, earning a high score for content density despite minor length.

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 no output schema, the description adequately describes return values (score breakdown, stats, disclaimer). With one parameter explained, it covers the tool's main facets, though some output format details are implicit.

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?

With 0% schema description coverage, the description fully explains the lone parameter 'include_history', detailing its effect (returns daily score series with prices) and default behavior. This adds significant value beyond the schema.

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 computes a composite fundamental pressure score for US natural gas, listing its components and range. It distinguishes from siblings ('get_production_nowcast', 'get_storage_nowcast') by focusing on pressure score rather than nowcasts.

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 includes a disclaimer that it's monitoring context, not trading advice, and shows no predictive edge. However, it lacks explicit guidance on when to use this tool versus alternatives, leaving the agent to infer from context.

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

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

Discloses that the nowcast is estimated using YoY trend anchored to news, and that demo scope hides the newest month's estimate. No annotations present, so description carries full burden. This provides transparency about data freshness and methodology.

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 concise sentences: first states core purpose, second adds methodology, third notes a limitation. No filler, front-loaded with key info.

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?

Provides methodology and limitation, but lacks explicit output structure details (e.g., date range, format of series). With no output schema, more explicit formatting information would be beneficial for the agent.

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?

No parameters exist; schema coverage is 100% implicitly. Description does not add parameter-specific information, which is appropriate. Baseline score of 3 applies.

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?

Clearly states it provides a nowcast of US dry gas production in Bcf/d on daily/monthly basis, with estimation methodology explained. The resource is distinct from sibling tools like 'get_storage_nowcast'.

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?

No explicit when-to-use or when-not-to-use instructions relative to sibling tools. The description states that demo scope hides the newest month's estimate, but does not guide the agent on scenario selection.

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

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

No annotations provided, so description carries full burden. It discloses return of pending estimates, verified data, and backtest stats, and that demo scope only includes published actual. However, it lacks information on whether the operation is read-only, authentication needs, 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence covering multiple aspects, front-loaded with the core purpose. It is concise but could be better structured for easier parsing.

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?

No output schema, so description must convey return data. It mentions headline, pending, last_verified, and accuracy stats, which is adequate but lacks details on data format, time units, and exact field names.

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?

Input schema has no properties, so baseline 4 applies. No parameters to document, and the description does not need to add parameter information.

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?

Description clearly states the tool returns EIA weekly natural gas storage data, including headline, pending estimate, verified data, and accuracy stats. It distinguishes between 'pro scope' and 'demo scope' and is distinct from sibling tools like get_fundamental_score and get_production_nowcast.

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?

Implies usage context (natural gas storage estimates) and differentiates pro vs demo scope, but does not explicitly state when to use this tool over siblings or provide exclusions.

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