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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds real substance beyond that: the 0–100 scale with 50 as neutral, the 5-year self-comparison baseline, and that output includes evidence trades and SEC links. It doesn't discuss data lag or what happens when history is too short.

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?

Two sentences, front-loaded with the score-and-explain core, then the trigger queries. The factor list is long but each item carries distinct meaning; no filler is present.

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?

An output schema exists and annotations cover safety, so the description only needs to frame intent and interpretation — which it does, including how to read the score. Only minor gaps (data coverage limits, behavior on sparse insider history) remain.

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 100% — both ticker and days are documented in the schema with range and example. The description adds no further parameter semantics (e.g., how the days window interacts with the 5-year comparison baseline), so the baseline 3 applies.

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?

States a precise verb+resource+output: 'Score current insider behavior for one company (0–100, 50 = neutral) and EXPLAIN it', then enumerates the exact factors composing the score. That clearly separates it from raw-list siblings like get_insider_activity or find_insider_clusters, though no sibling is named explicitly.

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?

Gives concrete trigger questions ('is insider activity at X bullish or bearish?', 'anything unusual about insiders at X?') that make the intended use unambiguous. It stops short of exclusions or naming which sibling to use for raw trade lists or individual insiders.

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