submit_feedback
Request a tool/feature or report an issue. FREE. High-volume requests get built first — this is how you shape Cerberus's roadmap.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| tool | No | ||
| message | Yes | ||
| requested_capability | No |
Request a tool/feature or report an issue. FREE. High-volume requests get built first — this is how you shape Cerberus's roadmap.
| Name | Required | Description | Default |
|---|---|---|---|
| tool | No | ||
| message | Yes | ||
| requested_capability | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It only states it's 'FREE' but does not disclose any side effects, return behavior, or whether feedback is stored/sent. Significant gaps.
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?
Two sentences, front-loaded with purpose, no wasted words. Efficient and to the point.
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?
Tool is simple, but description lacks parameter explanations and post-submission behavior. For a feedback tool, users need to know what happens after submission. Incomplete given no output schema.
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 has 3 parameters with 0% description coverage. Description only mentions 'tool/feature' and 'issue', leaving the 'tool' parameter unexplained. No format or constraints provided.
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?
Description clearly states the tool's purpose: 'Request a tool/feature or report an issue.' It uses specific verbs and resources, and distinguishes from sibling tools (all check/verify 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?
Description provides context ('FREE. High-volume requests get built first') and implies usage for shaping the roadmap. No direct alternative is needed since no sibling tool overlaps in functionality.
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 distinct resource and action: address checks, token checks, price analysis, transaction simulation, path finding, wallet history, pool discovery, attestation, and monitoring all have clear boundaries. While some tools share domain (e.g., check_xrpl_token vs resolve_asset), their purposes are clearly differentiated in descriptions.
Nearly all tools follow a verb_noun pattern (check_*, get_*, verify_*, analyze_*, explore_*, find_*, quote_*, watch_*, submit_*). The only slight deviation is 'token_holders', a noun phrase, but it is still concise and follows the same lowercase snake_case style, so it does not create confusion.
20 tools is on the heavier side of the ideal range, but the server's scope—cross-chain security, token analysis, monitoring, attestation, and market data—justifies this breadth. Each tool covers a distinct sub-domain, so the count is reasonable though slightly above the typical 3-15 sweet spot.
The tool surface comprehensively covers the domain: token discovery, safety, identity, price, holders, monitoring, address/issuer risk, transaction simulation, route finding, wallet activity, endpoint trust, and attestation. There are no obvious dead ends; users can discover tokens, verify them, track them, and receive alerts—a full lifecycle for crypto risk assessment.