Zyberno — Brina Gap stock analysis

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

No annotations are provided, so the description must carry the full burden. It adequately conveys that the tool is read-only ('analyzes') and lists the analysis outputs. However, it does not disclose potential side effects like API calls or data freshness, and there is no mention of symbol validity handling.

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, information-dense sentence that front-loads the purpose and lists key outputs without unnecessary words. It earns a high score for being concise and well-structured.

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 the single parameter and no output schema, the description provides a comprehensive list of expected outputs (Brina Gap, Margin of Safety, etc.). It is complete enough for an agent to understand what the tool returns, though it assumes domain knowledge of 'Zyberno' and 'Brina Gap'.

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?

The input schema has 100% coverage with a clear description for the only parameter ('symbol'). The description does not add extra semantics beyond what the schema already provides, resulting in an adequate but not superior score.

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 performs a 'Full Zyberno analysis for one US ticker' and enumerates specific outputs like Brina Gap, Margin of Safety, and intrinsic value. This distinguishes it from sibling tools which focus on narrower aspects like movers or valuation.

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 implies use when a comprehensive analysis of a single US stock is needed, but it does not explicitly state when not to use it or provide alternatives . The existence of sibling tools (get_brina_gap_movers, get_market_valuation) suggests they are for more specific needs, but the description lacks direct guidance.

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 are provided, so the description carries the full burden. It mentions the data is 'updated from SEC filings' but lacks details on update frequency, authorization needs, or performance implications. This is minimal transparency for a read tool.

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 two sentences, clearly front-loaded with the tool's output, and every phrase adds value. No redundancy or wasted words.

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 exists, but the description explains the two categories (Double Discounts and value traps) and that results are updated from SEC filings. It does not detail the exact output format (e.g., list of tickers or full data), but for a simple parameterless tool, it is mostly complete.

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?

The tool has zero parameters, so the description does not need to explain parameter details. The baseline for 0 parameters is 4, and the description adequately covers the tool's purpose without needing parameter semantics.

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 returns stocks flagged by the Brina Gap framework, specifically Double Discounts and value traps. It distinguishes from sibling tools like analyze_stock and get_market_valuation by focusing on a predefined screener output.

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 implies the tool is for obtaining current Brina Gap picks but does not explicitly state when to use it versus alternatives like analyze_stock. No guidance on exclusions or conditions is provided.

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?

The description explains the composite nature (multiple indicators) but lacks details on data availability, update frequency, or limitations. With no annotations, more behavioral disclosure would be beneficial.

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 that efficiently conveys the purpose and composition. No wasted words.

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?

For a parameterless tool returning a single score, the description is sufficient. It names the components and the range. However, it does not mention the return format (e.g., JSON object with a score field), but that is acceptable given simplicity.

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 zero parameters, so the description does not need to explain them. Schema coverage is 100% trivially. Baseline for 0 parameters is 4.

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 provides a US market valuation score (0-100) combining multiple indicators. It distinguishes itself from sibling tools like analyze_stock (individual stocks) and get_brina_gap_movers (market movers).

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 implies use for overall market valuation but does not explicitly state when to use this tool versus alternatives. No exclusion criteria or when-not-to-use guidance is provided.

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