ticker_report

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

With no annotations, the description carries the burden of behavioral disclosure. It discloses the covered universe (S&P 500 / Nasdaq 100 / major US ETFs), the filtering possibility, the ordering of patterns (newest first), and the paid-key field (hist_win_w20). This goes well beyond a generic 'returns data' statement. It does not mention rate limits or auth, but for a read-only report tool the disclosed behaviors are substantial.

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 compact and front-loaded: the first sentence states the tool's purpose, then Args and Returns sections add necessary detail. Every sentence earns its place, and the null-meaning clarification is high-value. No fluff or repetition of the schema.

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 single-parameter read tool with an output schema, the description is nearly complete. It explains the symbol format, the covered universe, null semantics, and result ordering. The only minor gap is that it doesn't describe the pattern objects' fields beyond hist_win_w20, but the output schema likely covers that. Overall, an agent can call this tool correctly with high confidence.

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?

Schema coverage is 0%, so the description must compensate. It explains the symbol parameter's format ('A US ticker, e.g. "AAPL"'), case-insensitivity, and the universe constraint. It also explains the return fields' semantics (deviation null meaning, patterns ordering). This is strong compensation for a single-parameter tool, though it could add more detail on pattern fields.

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 opens with a clear, specific statement: 'Everything held on one symbol: its current distance from its own ​200-day moving average, and the chart patterns most recently detected on it.' This names the resource (one symbol) and the two concrete outputs, distinguishing it from sibling tools like deviation_ranking or market_stretch. It is not a tautology and gives an agent a precise sense of what the tool returns.

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 explains the symbol argument format and case-insensitivity, and clarifies the meaning of a null deviation ('not covered', not 'no deviation'). It does not explicitly state when to prefer this tool over siblings, but the scope ('Everything held on one symbol') implies it is the per-symbol detail tool versus ranking/overview siblings. Clear context, but no explicit exclusions or alternatives.

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