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energy-brief

Synthesizes real-time US energy market signals into an AI-written brief with regime classification and decision implications. Choose standard or concise output.

Instructions

AI-synthesized US energy market intelligence brief. Assembles 9 real-time signals from Yahoo Finance: WTI crude futures, Brent crude (with spread), natural gas (Henry Hub proxy), energy sector ETF (XLE), oil services ETF (OIH), ExxonMobil, Chevron, Marathon Petroleum, and Baker Hughes. Returns 52-week context, Brent/WTI spread, market-regime classification, and a 200-word GPT-4o-mini narrative covering oil regime, dominant risk, and agent decision implications. Seam: crownblock upstream $1.00/call — STALL at $0.65 with real-time futures data vs monthly averages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleNoOutput length. 'standard' = 200-word narrative (default). 'concise' = 100-word summary.
Behavior3/5

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

The description outlines inputs and outputs but does not disclose limitations, data freshness, error handling, or dependencies. Without annotations, the description carries the full burden but falls short of full transparency.

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

Conciseness3/5

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

The description is verbose and includes an unclear, seemingly unrelated line at the end ('Seam: crownblock upstream...'). It could be more concise without sacrificing key details.

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

Completeness4/5

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

The description comprehensively covers the return values (52-week context, spread, regime, narrative) and data sources, making it adequate for an agent to understand what the tool provides despite lacking an output schema.

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?

The single parameter 'style' is well-documented in the schema, and the description reiterates its effect (default 200 words, concise 100). No additional semantic value is added beyond the schema, meeting the baseline for high 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 clearly states the tool generates an AI-synthesized US energy market intelligence brief with specific components (9 Yahoo Finance signals, 52-week context, spread, regime, narrative). However, the unrelated last line about 'Seam: crownblock upstream...' may cause confusion, preventing a perfect score.

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

Usage Guidelines3/5

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

The description implies the tool is for real-time US energy market intelligence, but lacks explicit guidance on when to use it versus alternative tools like commodity-futures or macro-brief. No exclusions or alternatives are mentioned.

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

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