NatGasLens — US Natural Gas & Henry Hub Data

get_us_natural_gas_market_brief

Read-onlyIdempotent

START HERE for any US natural gas / Henry Hub question: the whole dashboard in one call, so an agent does not have to chain five tools and stitch the numbers itself.

Returns, as of the latest data we hold: (1) pressure — every fundamental
we track (LNG feedgas, liquefaction outages, weather-model shifts, the
EIA injection pace, power burn vs normal, NOAA cooling demand, total
demand week-over-week) with its direction on price, strength, the number
behind it and a plain-English sentence, plus an overall roll-up naming
which signals push down and which push up; (2) demand — total US demand
in Bcf/d with its components (power burn, LNG feedgas, industrial,
residential+commercial, Mexican exports, other), the change against the
same weekday a week ago, per-component week-over-week deltas, power burn
year-over-year, and supply minus demand; (3) storage, production, the
Henry Hub forward curve six months out and CFTC managed-money
positioning, each reduced to its latest reading.

Also returns `note` — the rules for reading these numbers correctly:
demand has a weekly profile so day-to-day moves are noise and only
week-over-week comparisons mean anything, the monthly EIA components are
flat steps rather than live signals, and the curve and positioning are
context, not a forecast. Long histories and daily series are deliberately
left out; fetch the dedicated tool when you need one.

Direction is the sign of a deviation from normal, not a probability that
price moves. Market analysis, NOT investment advice. Demo scope returns
the same shape on delayed data.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`asof`	No
`data`	No
`note`	No
`tool`	No
`scope`	No
`stale`	No
`disclaimer`	No

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already mark this as a safe, idempotent, read-only operation, and the description adds substantial behavioral context: the 'note' clarifies week-over-week vs day-to-day interpretation, flat monthly steps, context-not-forecast framing, direction-as-deviation-not-probability, and demo scope returning delayed data on the same shape. This goes well beyond the annotations without contradicting them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is long but well-structured and front-loaded with the key purpose. Each section—purpose, return contents, interpretation rules, exclusions—earns its place, and the numbered return list makes scanning easy. Slightly more verbose than strictly necessary, but not wasteful.

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

Completeness5/5

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

Given the tool's broad aggregate scope, the description is remarkably complete: it lists all return components, provides the correct reading of those numbers, warns about data freshness in demo mode, and explicitly states exclusions. The existence of an output schema further reduces the need to describe return shapes, so this description fully equips an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the baseline is 4. The description effectively explains what the no-argument call returns, which is sufficient; there are no parameter details to add.

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

Purpose5/5

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

The description opens with 'START HERE for any US natural gas / Henry Hub question' and calls itself 'the whole dashboard in one call,' making its aggregate purpose unmistakable. It clearly distinguishes itself from siblings by stating an agent does not need to chain five tools, and it enumerates exactly what data sections are returned.

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

Usage Guidelines4/5

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

The description explicitly says to start here for any US natural gas/Henry Hub question, and it gives a when-not case: 'Long histories and daily series are deliberately left out; fetch the dedicated tool when you need one.' However, it does not name specific alternative tools, so the guidance stops short of being fully explicit about which sibling to choose.

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

All NatGasLens — US Natural Gas & Henry Hub Data tools Inspect

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TDQS

A4.3/5.0

Disambiguation5/5

Each tool addresses a distinct aspect of natural gas data: fundamental score, production nowcast, and storage nowcast. There is no functional overlap, and agents can easily differentiate them.

Naming Consistency5/5

All tools follow a consistent 'get_us_natural_gas_<specific_measure>' pattern, using snake_case and clear descriptive names. The naming is uniform and predictable.

Tool Count4/5

Three tools cover key indicators for natural gas monitoring. While the set is concise, it avoids bloat and each tool adds significant value. A slight increase might be justified, but the current count is appropriate for the focused scope.

Completeness4/5

The tools provide core supply and demand indicators (production, storage, and a composite score incorporating demand). Minor gaps like a separate demand tool exist, but the composite score partially addresses them, making the surface fairly complete for monitoring purposes.

Resources

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