roast
roast_targetWitty roast of any target — wallet, tweet, idea, code, anything. $0.05 USDC.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| target | Yes | Anything to roast: wallet, tweet, idea, code, etc. |
roast_targetWitty roast of any target — wallet, tweet, idea, code, anything. $0.05 USDC.
| Name | Required | Description | Default |
|---|---|---|---|
| target | Yes | Anything to roast: wallet, tweet, idea, code, etc. |
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?
While annotations declare readOnlyHint and openWorldHint, the description adds important behavioral context: the tool charges $0.05 USDC, which is a significant side effect not covered by annotations. It also sets expectations for a 'witty' tone. This goes beyond what annotations already provide.
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, highly concise sentence that captures scope, tone, and cost with no wasted words. It front-loads the core action ('Witty roast') followed by examples and pricing.
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 only one parameter and no output schema, the description sufficiently covers what the tool does and its cost. It does not explain response format, but for a simple roast generator this is less critical. The examples provide enough context for an agent to decide when to invoke it.
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 coverage is 100% with the target parameter described as 'Anything to roast: wallet, tweet, idea, code, etc.' The description reinforces this by listing examples, but it does not add new semantic detail beyond what the schema already provides. Baseline 3 is appropriate.
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 explicitly states the tool performs a 'witty roast of any target' and lists concrete examples (wallet, tweet, idea, code). This clearly distinguishes it from siblings like grade_target or screen_wallet by emphasizing humor/roasting rather than evaluation or screening.
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 usage by saying 'any target' and gives examples, but it does not explicitly state when not to use this tool or mention alternatives. Context from sibling names (e.g., grade_target) suggests alternatives, but no direct comparison is provided.
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.
Each tool targets a clearly distinct function — anchoring, decoding, wallet intelligence, entertainment, etc. Even similar tools like decode_calldata vs decode_tx and intel_wallet vs screen_wallet are precisely separated by descriptions.
Most names follow a verb_noun pattern (anchor_hash, decode_calldata), but there are exceptions like aura_read (noun_verb), intel_wallet (noun_noun), and ledger_report (ambiguous). This mixed convention is readable but not fully consistent.
18 tools is slightly above the ideal range but not overwhelming. Each tool serves a specific purpose, and the count feels reasonable for the broad set of utilities offered.
The core utilities (anchoring, wallet intelligence, ledger accounting) are well-covered without obvious dead ends. Some domain-specific workflows could be expanded (e.g., verifying anchors), but the existing tools provide complete standalone operations.