Automates $AERO locking, epoch gauge voting, and bribe reward harvesting on Aerodrome ($0.01 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| amount | No | ||
| tokenId | No | ||
| lockDurationWeeks | No | ||
| poolVoteAddresses | No |
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?
No annotations are provided, so the description must disclose that this automates on-chain operations—sending transactions, locking tokens, changing positions, claiming bribes—but it never mentions side effects, permissions, gas, or reversibility. The 'Automates' wording hints at mutation but does not explain consequences.
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 single sentence is compact and readable, but the parenthetical '($0.01 USDC)' is unexplained and adds noise; the description could be tighter and more informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a multi-action tool with five parameters and no annotations or output schema, the description gives no per-action requirements, constraints, or expectations about what the agent will receive. An agent cannot reliably construct a valid call without opening each enum value and guessing parameter combinations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only offers broad concepts ('locking,' 'voting') rather than explaining amount, tokenId, lockDurationWeeks, or poolVoteAddresses. The action enum carries most of the semantic weight.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a concrete set of operations—'$AERO locking, epoch gauge voting, and bribe reward harvesting'—and the action enum reinforces that this is a veAERO governance/locking tool. It is clearly distinguishable from swap and CLAMM siblings, though it doesn't explicitly name an alternative.
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?
No guidance is provided on when to choose this over siblings such as aerodrome_swap, aerodrome_clamm, or get_aerodrome_yields. The intended context is only implied by listing protocol activities.
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.