ton_protocol_health
Protocol health: TVL, audits, risk grade (DeDust, Ston.fi, Tonstakers, EVAA)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| protocol | Yes | Protocol name |
Protocol health: TVL, audits, risk grade (DeDust, Ston.fi, Tonstakers, EVAA)
| Name | Required | Description | Default |
|---|---|---|---|
| protocol | Yes | Protocol name |
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 carries the full burden for behavioral disclosure. It names the data points returned (TVL, audits, risk grade) but does not disclose whether the tool is read-only, any permission requirements, error behavior for invalid protocol names, or response format details. This falls short for an unannotated tool.
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 sentence that uses a colon efficiently to list key output metrics and protocol examples. Every word earns its place, with no fluff or redundancy. It is appropriately sized for a one-parameter lookup tool.
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 low complexity (1 param, no output schema, no annotations), the description covers the essential purpose and output fields, but remains incomplete. It does not specify whether the listed protocols are exhaustive, how to format the protocol name (e.g., case sensitivity), or what happens for unsupported protocols. This is adequate but leaves clear gaps.
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 describes 'protocol' as 'Protocol name' with 100% coverage, but the description adds meaningful context by listing specific protocol examples (DeDust, Ston.fi, Tonstakers, EVAA). This helps the agent infer likely valid values and the tool's scope, going beyond the schema's generic label.
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 indicates the tool provides protocol health metrics (TVL, audits, risk grade) and names specific protocols, making its purpose unambiguous. However, it lacks an explicit verb like 'get' or 'fetch', so it's a noun-phrase description rather than a full action statement. It distinguishes from sibling tools by focusing on health metrics rather than yields or volume.
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 gives no explicit guidance on when to use this tool versus alternatives. It implies use when protocol health data is needed, but does not mention alternatives, exclusions, or scenarios where another tool would be more appropriate. With ten sibling tools, this lack of differentiation guidance is a notable gap.
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 aspect of TON (e.g., bridge flows, DeFi yields, protocol health, transactions) with no overlapping purposes, making selection unambiguous.
All tools follow a consistent 'ton_' prefix with descriptive snake_case noun phrases (e.g., ton_network_stats, ton_dex_volume), ensuring predictable naming.
With 11 tools, the count is well-scoped for a blockchain analytics server, covering key aspects without being overwhelming or sparse.
The set covers network stats, wallet, transactions, DeFi, DEX, protocol health, stablecoin risk, and jettons, but may lack NFT or staking analytics.