aerodrome_swap
Executes low-slippage token swaps directly via Aerodrome Finance Router on Base Mainnet ($0.01 USDC)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| tokenIn | Yes | ||
| amountIn | Yes | ||
| isStable | Yes | ||
| tokenOut | Yes | ||
| decimalsIn | Yes |
Executes low-slippage token swaps directly via Aerodrome Finance Router on Base Mainnet ($0.01 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| tokenIn | Yes | ||
| amountIn | Yes | ||
| isStable | Yes | ||
| tokenOut | Yes | ||
| decimalsIn | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions 'low-slippage' and execution, but omits critical details such as slippage tolerance, potential reverts, gas costs, approval requirements, or the exact fee structure. For a financial transaction tool, this is insufficient transparency.
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, front-loaded sentence that conveys the primary action quickly. However, it is so brief that it sacrifices necessary structure—there is no breakdown of steps, parameters, or behavior. It is concise but not 'appropriately sized' for a swap tool with this complexity.
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 financial nature (token swaps), 5 parameters, no output schema, and no annotations, the description is drastically incomplete. It fails to explain return values, error behaviors, slippage handling, or any parameter details. An agent cannot call this tool correctly with the information provided.
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 has 5 parameters with 0% description coverage. The description does not explain any parameter meaning, such as what amountIn represents (units, wei, decimals), why decimalsIn is needed, or what isStable controls. The tool description adds no value here, leaving agents to guess parameter semantics.
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 a specific verb ('Executes'), a resource ('token swaps via Aerodrome Finance Router'), and a network context ('Base Mainnet'), with an example fee. It is easily distinguishable from sibling tools like get_aerodrome_yields (yields, not swaps) and other unrelated tools.
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 implies when to use the tool (for token swaps on Aerodrome) but provides no explicit guidance on when not to use it or what alternatives exist. It does not mention that get_aerodrome_yields might be more appropriate for yield-related tasks, nor does it state any prerequisites such as token approval or liquidity requirements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tools are largely distinct, but web_scraper and browser_scraper overlap on web page scraping, and data_feeds and public_data_feed are hard to distinguish without more detail. A few descriptions do help separate output formats, but an agent could still misfire.
All names use snake_case and are descriptive, but the naming pattern is mixed: deploy_contract and render_screenshot are verb-first, while smart_contract_verifier, base_analytics, and data_feeds are noun phrases. This prevents a predictable verb_noun convention.
Twelve tools is a reasonable count and each has a defined paid purpose. However, the set spans scraping, data feeds, DeFi yields, and smart-contract deployment, so it feels slightly broad for a single server.
Core operations exist for scraping, extraction, deployment, verification, and data feeds, but the surface is incomplete for lifecycle workflows: contracts can be deployed but not called/managed, and data feeds cannot be listed or refreshed. The gaps are noticeable but not fatal for independent one-off API calls.