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Glama

biii

by io.github.philpof102-svg

till_funder_history

HAS THE WALLET THAT PAID FOR THIS LAUNCH ALREADY KILLED ONE? till_launch_funder reads the graph and tells you a cluster exists; this reads our OWN observation record and tells you what happened to the rest of it. The distinction matters because every other check here asks the token a question it cannot answer in time: a curated security index returns an owner address for roughly one Base token in ten, so "who can still fire a rug power" — the question this whole scanner was built on — came back unanswerable on 221 of 221 launches we watched. Who PAID is answerable, because we watched that ourselves. THE EVIDENCE IS WALK-FORWARD, which is the only kind worth quoting: every token was replayed in time order and judged using strictly earlier history, so no prediction ever saw its own outcome or any later one. A payer with a prior kill was followed by another death in 62 of 67 resolved cases (93%) against a 52% base rate, and it holds across SIX independent payers, each 75-100% lethal — not one outlier carrying an average. Read the limits as part of the answer: six operators is not sixty, "clean so far" rests on two payers and is an absence of a bad record rather than a good one, and 47% of watched launches have no funder on file — but 96% of THOSE were never traced at all, because tracing is capped per run, so that number measures our own budget and not the chain; they are reported as out of reach rather than safe, and never as evidence. AND IT IS EVADABLE FOR THE PRICE OF ONE HOP — a fresh funding wallet lands in "never seen", which is already 30% of cases. It makes REUSE expensive, which is what an operation running dozens of launches an hour actually does; expect the strong bucket to decay as operators adapt. Structure, never intent: a shared funder proves shared control or shared infrastructure, and a launchpad looks identical from the graph. Every answer carries the age of the database, and past the freshness bar the reassuring verdicts are WITHDRAWN rather than annotated, because a stale "never killed" is the exact sentence that gets someone hurt. Pure, offline, read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
funderNothe wallet that PAID for the launch — get it from till_launch_funder, which traces deployer→funder on chain. Omit it and the honest answer is that this check has nothing to say.

Schema Changelog

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

  1. 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, the description fully discloses behavior: it is 'pure, offline, read-only,' withdraws reassuring verdicts past freshness, is evadable with one hop, and has known statistical limitations. It also explains interpretation pitfalls like shared infrastructure vs. intent. This goes far beyond typical descriptions.

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

Conciseness2/5

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

The description is a single, dense paragraph with extensive statistical evidence and caveats. It lacks structure (no breaks, sections, or bullets) and is far longer than necessary, burying the core message under detailed performance data. This reduces quick comprehension.

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

Completeness4/5

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

The description thoroughly covers purpose, usage, reliability, and pitfalls, which is comprehensive given the tool's complexity. However, it does not explicitly state the format or type of output (e.g., a label, score, or report), which is a minor gap since there is no output schema to clarify this.

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

Parameters5/5

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

The 'funder' parameter is fully described in the schema, and the description adds meaning by explaining where to get it (till_launch_funder), what it represents, and what happens if omitted. The main description enriches the parameter's significance in the context of prior kills.

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 opening question 'HAS THE WALLET THAT PAID FOR THIS LAUNCH ALREADY KILLED ONE?' clearly states the tool's purpose. It explicitly distinguishes itself from till_launch_funder by noting it uses the internal observation record rather than the graph, making it specific and differentiated from siblings.

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

Usage Guidelines5/5

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

The description explicitly says to get the funder from till_launch_funder, and warns that omitting it yields 'nothing to say.' It also explains when results are unreliable (stale database, evadable via fresh wallets) and notes that the tool should be used as a complement to other checks, giving clear context for when to use it.

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