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Glama

biii

by io.github.philpof102-svg

till_vet_meme

Which contract is the REAL memecoin among 10+ look-alikes? Fail-closed verdict from live market data (DexScreener). Returns: genuine (one contract dominates liquidity), ambiguous (top-2 tied — never certified), impersonation (the address you passed is NOT the dominant one), thin (no credible liquidity). Advisory + re-verifiable. ALSO returns observedRisk, kept SEPARATE from the verdict on purpose: status answers IDENTITY ("is this the contract you think it is?"), observedRisk carries what this node has MEASURED about outcomes. Its rate is WITHHELD unless the bound is verified — the reading was only measured where the launch funder had paid fewer than 20 sibling wallets, and outside that branch it separates almost nothing, so a number there would be a ceiling dressed as a signal. The bound is checked for free against this node's own observation database; pass siblingCount yourself if you have traced the funder. Every shape carries siblingCountSource (where the number came from) and a disclosure: it is a POPULATION statistic, never a claim that this particular token will rug. inSample has THREE states, not two: true (the caller told us the bet has graded nothing forward yet), false (it has graded some), and null (nobody supplied the count — UNKNOWN, which is not the same as zero, and the accompanying gradedForwardNote says so).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesmemecoin symbol, e.g. "TOSHI", "BRETT"
addressNooptional specific contract address to judge
chainIdNooptional chain filter — the DexScreener slug ("base", "solana", "ethereum") or an EVM chain id (8453 = Base). A chain we cannot map returns NO candidates rather than silently searching every chain: being handed a Solana contract after asking for Base is worse than being handed nothing.
siblingCountNooptional: how many sibling wallets the launch funder has paid, if YOU have traced it. Supplying it lifts the withholding on `observedRisk`. Omit it and this node checks its own observation database for free; omit it AND the token is unknown here, and the rate stays WITHHELD rather than guessed.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / properties / siblingCount
      Added value: +{
+  "description": "optional: how many sibling wallets the launch funder has paid, if YOU have traced it. Supplying it lifts the withholding on `observedRisk`. Omit it and this node checks its own observation database for free; omit it AND the token is unknown here, and the rate stays WITHHELD rather than guessed.",
+  "type": "number"
+}
  2. Changed2 schema fields changed
    • changedInput schema / properties / chainId / description
      Previous value: -"optional chainId filter (e.g. 8453 for Base)"New value: +"optional chain filter — the DexScreener slug (\"base\", \"solana\", \"ethereum\") or an EVM chain id (8453 = Base). A chain we cannot map returns NO candidates rather than silently searching every chain: being handed a Solana contract after asking for Base is worse than being handed nothing."
    • changedInput schema / properties / chainId / type
      Previous value: -"number"New value: +[
+  "string",
+  "number"
+]
  3. First observed

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description fully carries the burden of behavioral disclosure. It reveals fail-closed verdict behavior, the exact meaning of each verdict category, the withholding logic for observedRisk, the three-state inSample semantics, and the caveat that siblingCountSource is a population statistic, not a claim about a specific token. This is exceptionally transparent for a complex tool.

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?

The description is long and dense, but every sentence provides critical operational detail. It starts with a clear purpose, then lays out verdicts, risk withholding logic, and inSample states. Some rhetorical phrasing could be tightened, but the information is well-structured and front-loaded with the core purpose.

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

Completeness5/5

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

There is no output schema, so the description must explain return values, and it does thoroughly: verdict categories, observedRisk conditions, siblingCountSource, and inSample states. For a tool with 4 parameters and no output schema, this is comprehensive and leaves few gaps in understanding the tool's behavior.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds meaningful context beyond the schema by explaining how siblingCount impacts the observedRisk withholding and reinforces the chainId behavior (unmapped chain returns no candidates). It doesn't add much for symbol or address, but the added semantics for siblingCount are valuable.

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

Purpose5/5

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

The description clearly states the tool's purpose: to identify the real memecoin contract among look-alikes using live market data from DexScreener. It specifies the resource (memecoin contract) and the action (vet/judge authenticity), and distinguishes itself from sibling tools like till_vet_asset and till_vet_merchant by focusing on memecoins.

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?

The context is clear: this tool is used for vetting memecoin contracts among multiple look-alikes. It implies when to use it (when dealing with memecoins with potential impersonations) but does not explicitly list exclusions or alternative tools. Given the sibling names, the use case is well-scoped, though not explicitly contrasted.

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

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TDQS

B3.1/5.0
Disambiguation3/5

Many tools have distinct, well-named purposes (vet_agent vs vet_merchant), but there is notable overlap between till_trust and till_vet_merchant (both provide trust verdicts), and till_launch_funder vs till_funder_history are closely related. The descriptions are detailed enough to differentiate, but an agent could still misselect between a few pairs.

Naming Consistency3/5

All tools share the till_ prefix, but the pattern is mixed: some use verb_noun (check_invoice, create_charge, watch_wallet) while others are noun phrases (key_exposure, open_approvals, rug_powers) or bare nouns (floor, trust, roll). This is readable but not predictable, so an agent cannot reliably guess a tool name from a verb.

Tool Count2/5

At 29 tools, this server exceeds the 25+ threshold that signals an overgrown toolkit. Even with a broad domain, many tools are one-off niche scanners (till_b20_authentic, till_floor, till_meter) that inflate the surface and could be consolidated or externalized.

Completeness4/5

The toolkit covers the payment lifecycle comprehensively: create charges/invoices, check payments, verify delivery, generate receipts, rolls, and accounting exports. It also spans identity, trust, security scanning, and theft tracing. Minor gaps exist (no update/cancel for charges, no token-general vetting), but the non-custodial, read-only design makes these acceptable.

Resources