ln_anomaly_check

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

With no annotations, the description carries the burden. It discloses that the tool compares against historical averages and returns a verdict (normal/high/first_time) with context and average. It does not mention error handling or side effects, but the core behavior is transparent.

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 (~70 words), with a clear structure: one-line purpose, usage note, args list, return summary. Every sentence adds value, and the most critical info is front-loaded.

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 no output schema, the description adequately covers inputs and returns. It lacks explicit error cases or edge behavior (e.g., unknown vendor), but for a straightforward anomaly check tool, the level of detail is sufficient.

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% (no descriptions in schema), but the description compensates by explaining vendor (name/domain) and amount_sats (proposed payment in satoshis). This adds meaning beyond the type declarations.

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's purpose: 'Check if a proposed payment amount is normal for a vendor.' It specifies the verb (Check) and resource (payment amount anomaly), and distinguishes from siblings like ln_budget_check by focusing on price anomaly vs historical averages.

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 explicitly says 'Use this before making a payment to catch price anomalies,' providing clear context. It does not explicitly exclude alternatives, but the usage is well-defined and sufficiently distinct from sibling tools.

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