get_trust[FORENSICS] Trust / scam-risk screen for a token: resolves the ticker to a contract via DexScreener, then checks GoPlus Security for honeypot behavior, mint function, high taxes, and insider concentration. Run this BEFORE taking any alt-coin signal seriously — a bullish read on a honeypot is worthless. Mirrors REST /trust/{coin}. Analytical data only, not financial advice.
| Name | Required | Description | Default |
|---|---|---|---|
| coin | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it read-only, and the description adds that the tool depends on external services (DexScreener, GoPlus Security) and inspects specific token properties. It omits rate limits or failure behaviors, but provides substantial operational context beyond the annotation.
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 four tight sentences: purpose, usage trigger, REST mirror, and disclaimer. It is front-loaded with the primary function and has no redundant words.
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?
With one parameter and no output schema, the description covers the input, the procedure, and the practical context. The return format is not explicitly described, but the evaluative checks make it predictable enough for an agent to invoke correctly.
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 only names the parameter 'Coin' with no description, but the description clarifies it is a ticker that gets resolved to a contract, giving the agent the exact input format. This fully compensates for the zero schema coverage.
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 uses a specific verb ('screen') and resource ('token'), lists exact checks (honeypot, mint, taxes, insider concentration), and distinguishes itself from sibling market-analysis tools by framing itself as a pre-trade forensics step. The phrase 'Run this BEFORE taking any alt-coin signal seriously' makes its unique role unmistakable.
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?
It explicitly states when to use the tool: before acting on any alt-coin signal, labeling it a forensics/scam-risk gate. It does not name alternatives or state when not to use it, so it earns a 4 rather than a 5, but the trigger is decisive.
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.
Most tools have clearly distinct purposes with detailed descriptions, but there are clusters of similar concepts (e.g., get_liquidity_map vs get_liquidation_map, get_state vs get_state_brief, multiple signal-related tools) that could cause misselection despite thorough documentation.
All tools follow a consistent lowercase verb_noun pattern, predominantly get_* nouns, with only a few non-get verbs like list_signals, rank_trades, log_trade, etc., but the style is uniform.
With 52 tools, the surface is extremely heavy for an agent to navigate. While the server's scope is broad, the count far exceeds the typical 3-15 range and falls into the 'too many' category.
The tool set covers the full lifecycle for journaling, signals, market analysis, and proof, with no major dead ends. Minor gaps exist, such as no dedicated get_trade_by_id (workaround via get_journal) and no get_market_state tool despite being referenced in get_state.