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

With no annotations provided, the description carries the burden of behavioral disclosure. It does disclose key methodology (vetted realized-PnL winner seed set, bot-filtered, ranking by distinct smart buyers + recency), which adds value. However, it lacks details on data freshness, update frequency, or limitations (e.g., how 'proven-winner' is defined, potential biases), leaving room for ambiguity.

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 (two sentences) and front-loaded with the core question. It packs significant information without wasted words. However, the use of jargon ('aping', 'trenches', 'pre-ape') might reduce clarity for some users, though it remains efficient. No unnecessary fluff.

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 4 fully described parameters, no annotations, and no output schema. The description covers the purpose, methodology, and ranking order, which is fairly complete for a screening tool. However, it does not specify the output format (e.g., what fields are returned for each token), which the description would need to compensate for the missing output schema. This gap prevents a higher score.

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 100%, so the baseline is 3. The description adds minimal parameter-specific semantics beyond what's in the schema; it mentions 'fresh (<6h)' corresponding to max_token_age_hours and 'recent buys' aligning with hours_back, but these are already clearly documented in the schema. No additional meaning is needed.

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 what the tool does: identifies proven-winner wallets aping fresh (<6h) memecoin launches and what they are buying. It distinguishes itself from siblings by emphasizing 'vetted realized-PnL winner seed set (bot-filtered)' and 'Pre-ape attention signal', making it unique among similar tools like smart_money_flow or copy_trade_signals.

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 clear context for when to use this tool—when looking for early signals of fresh memecoin launches being bought by proven smart wallets. It implies a niche use case (pre-ape attention) and differentiates from broader alternatives through terms like 'proven-winner wallets' and 'bot-filtered', but it does not explicitly state when not to use it or name alternatives.

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