detect_threshold_breaches

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

No annotations are provided, so the description carries the behavioral burden. It does a good job explaining the behavioral nuances (duration threshold, hysteresis logic) that govern the tool's detection output. However, it doesn't disclose what happens with missing data, how the JSON vs CSV data detection works, or error cases. The core detection behavior is well disclosed, but edge cases are left undocumented.

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 well-organized: purpose statement, key behavioral notes, Args list, and Returns section. It front-loads the critical compliance insight before diving into parameters. The Args and Returns sections are clearly structured. Slightly verbose with the compliance preamble, but every sentence adds value for a compliance-critical tool.

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?

The tool has 7 parameters with 0% schema coverage, but the description explains all of them with examples. An output schema exists, so the Returns description doesn't need full detail but still outlines what's returned (list of violations with type, start, end, duration, peak value, and summary). For a complex detection tool with nuanced semantics, the coverage is quite 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?

Schema description coverage is 0%, so the description fully compensates. Every parameter is explained: min_temp and max_temp with concrete examples (2.0 and 8.0 for 2-8°C products), None semantics for absent thresholds, min_duration_minutes meaning, hysteresis semantics, and ts_field/value_field purposes. The description adds substantial meaning beyond the bare schema field names.

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 it detects temperature threshold breaches (cold chain violations). It specifies the exact verb (wykrywa/detects), the resource (threshold breaches), and the domain (cold chain). It provides strong detail about what constitutes a violation (duration, hysteresis), which clearly distinguishes it from sibling tools like detect_anomalies and summary_stats.

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 key compliance semantics: brief momentary spikes often do NOT count as violations, only those sustained past min_duration_minutes count, and hysteresis prevents false repeated alarms. This gives clear context for when to trust the tool's output. However, it doesn't explicitly contrast with sibling tools like detect_anomalies, so there's no direct 'use this instead of X' guidance.

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