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Glama

check_token

Verify a crypto token's legitimacy before buying by checking contract addresses, links, or forwarded messages. Returns a risk verdict and red flags to avoid scams.

Instructions

Check if a crypto token is a scam before buying. text can be a contract address, a DexScreener or pump.fun link, or a whole forwarded "gem" message, on any of 64 networks (chain "auto" detects it; or pass a DexScreener chain id like "ton", "sui", "tron", "hyperevm"). Returns a rule-based verdict (LOW_RISK, CAUTION, HIGH_RISK, UNKNOWN), a 0-100 risk score, plain-language findings (lang "en" or "pcm" for Nigerian Pidgin), what you'd get back in naira, and red flags in the message itself.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoen
textYes
chainNoauto
amount_ngnNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. It discloses rule-based verdicts, risk score, language support, naira conversion, and chain auto-detection, but does not state whether the operation is read-only, requires authentication, or has rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the purpose, then packs parameter and return details efficiently. Dense but no filler sentences; could be slightly more structured for readability, but every clause adds information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, 0% schema coverage, and four parameters, the description covers much ground but misses amount_ngn semantics and safety profile. It is adequate but leaves clear gaps for an agent to call the tool fully correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains text inputs (contract address, links, forwarded messages), chain (auto or DexScreener ID), and lang (en/pcm), but completely omits the amount_ngn parameter and its default of 50000, leaving one of four parameters undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (check) and resource (crypto token scam) with clear intent. It does not explicitly differentiate from siblings like scan_message or token_history, which could also handle message or token analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context: use before buying to check if a token is a scam. It lists accepted input types (contract address, DexScreener/pump.fun link, forwarded message) but names no alternatives or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.