enrich_tokenAnalyze a Solana SPL token: price, market cap, liquidity, holder concentration (top 1/5/10%), slippage estimates at 4 position sizes ($100/$1K/$10K/$100K), risk flags, and Jupiter verification.
| Name | Required | Description | Default |
|---|---|---|---|
| mint | Yes | Token mint address (base58) | |
| include_holders | No | Include top 20 holders with balances and % supply |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It is transparent about the data analyzed and returned, and the verb 'Analyze' strongly implies a read-only operation. However, it does not explicitly state that the tool is non-destructive, nor does it mention any potential costs, rate limits, or data source dependencies, which would make it fully 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 a single, dense sentence that front-loads the core purpose and then lists all key analyses. Every element is informative, with no filler or redundancy. It is concise while conveying substantial detail.
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 the tool has no output schema, the description appropriately enumerates the expected return values and even specifies position sizes for slippage estimates. This provides enough context for an agent to invoke the tool and interpret results. It lacks some details about error cases or data sources, but overall it is fairly complete for its complexity.
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?
The schema already provides 100% documentation for both parameters (mint and include_holders), so the baseline is 3. The description adds no extra meaning to the parameters; it only highlights the holder concentration metric, which is an output, not a parameter insight. Thus, no value beyond what the schema gives.
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 uses a specific verb ('Analyze') with a clear resource ('Solana SPL token') and enumerates the exact metrics returned (price, market cap, liquidity, holder concentration, slippage, risk flags, Jupiter verification). This distinguishes it clearly from sibling tools like enrich_wallet or token_trend.
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 clearly implies when to use the tool: for deep token analysis, given the extensive list of metrics. However, it does not explicitly state when not to use it or mention alternatives like token_trend or compare_tokens, so it stops short of full usage differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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With 32 tools, several have overlapping purposes, such as wallet_history vs portfolio_history (both track wallet portfolio over time) and smart_money_flow vs smart_money_trenches (both follow smart money movements). However, most tools have clearly distinct scopes, and detailed descriptions help differentiate them.
All tool names follow snake_case with a predictable verb_noun or noun phrase pattern (e.g., enrich_token, compare_wallets, perps_market_trend). The consistent structure makes the set easy to navigate, even the 'perps_' prefix group is uniform.
32 tools is well above the 25-tool threshold, making the surface feel heavy. While the breadth reflects the wide domain of Solana analytics, the sheer number can overwhelm agents and increase the chance of selecting the wrong tool.
The tool set covers most aspects of Solana token/wallet/perp analysis, including enrichment, comparison, trend tracking, smart money flows, and perp market structure. Minor gaps exist, such as no direct historical OHLCV endpoint, but the existing tools handle core workflows well.