Measure compaction

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

Beyond the readOnlyHint/idempotentHint annotations, it discloses hard prerequisites (tenx CLI on PATH or LOG10X_TENX_PATH, Docker mode, SIEM credentials), the data-provenance chain, and confidence tiers keyed to event counts (high >=50, medium 10-49, low <10). This is exactly the behavioral context annotations cannot convey.

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?

Front-loaded with the core action and value, and most sentences earn their place. There is some redundancy, however, as the local-engine requirement is effectively stated twice ('Requires: tenx CLI installed locally...' and 'REQUIRES a local engine: the tenx binary on PATH, or Docker...').

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?

Because an output schema exists, return values needn't be explained, and the description still covers the full operational picture: prerequisites, environment scoping, confidence behavior, and integration with downstream savings tools. Nothing an agent needs to call it correctly is missing.

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 already 100%, so the baseline is 3, but the description adds real meaning: it ties sample_size to confidence quality ('high confidence requires >=50 events per pattern') and explains the cost tradeoff of larger samples. It also frames timeRange as the measurement window, going beyond the schema's format description.

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 states a specific verb and resource ('Measure real per-pattern compaction ratios from a SIEM sample') and explains the mechanism (pulls events, runs through local tenx engine, returns compaction_ratio_x). It explicitly differentiates from siblings by naming log10x_estimate_savings and log10x_pattern_detail as the tools whose generic estimates it replaces.

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?

It gives explicit routing: 'Use this to replace generic 5-10x estimates in log10x_estimate_savings and log10x_pattern_detail with measured values for this customer environment.' Prerequisites and the downstream flow into log10x_estimate_savings are stated, leaving little to inference.

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