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

With no annotations provided, the description carries the full burden. It discloses that results are market-adjusted vs CHZ, returns specific statistics (mean, t-stat, CI, etc.), and warns against using as advice. It explains the pooling behavior ('Omit a dimension to pool'). There are no contradictions. However, it does not mention any restrictions, rate limits, or authentication needs.

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 concise at three sentences, no wasted words. The first sentence effectively front-loads the core purpose and dimensions, the second lists outputs, and the third adds a critical behavioral note (pooling and disclaimer). Every sentence earns its place.

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 7-parameter tool with no output schema, the description adequately explains the core behavior, aggregation (pooling), and output fields. It does not mention default values (e.g., horizon_min default 30 is in schema but not description) but this is acceptable given high schema coverage. The warning 'descriptive history, not advice' adds important context.

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 high (86%), so the schema already documents most parameters. The description mentions the core dimensions but does not add extra meaning beyond what the schema provides. For example, 'scoreline_state' is described as 'Token team's state BEFORE the event' in the schema, and the description only says 'scoreline_state'. Thus, no additional value.

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 returns event-conditioned, market-adjusted token reaction profiles, specifying dimensions like event_type, event_side, minute, scoreline_state, and importance. It lists output statistics. However, it does not explicitly distinguish itself from sibling tools such as tokenintel_goal_direction_asymmetry or tokenintel_late_game_redcard_profile, so it lacks sibling differentiation.

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 provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or contexts where other tools might be more appropriate. The only clue is the phrase 'descriptive history, not advice,' which is insufficient for usage decisions.

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