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Glama

biii

by io.github.philpof102-svg

till_rug_powers

WHO CAN STILL RUG THIS TOKEN? till_vet_meme says which contract is the real one; this says whether the real one is itself a trap. A dangerous capability only counts if someone can still FIRE it — mintable with ownership renounced is inert, the same flag with a live owner is an armed rug, and scoring flags without that distinction is why most scanners are noise. Merges two sources that fail at opposite ends: a curated index (owner powers, LP locks) that has never heard of a token minted ten minutes ago, and a live trade simulation that always works on fresh deploys but sees nothing about control. Fail-closed: NEVER returns clean on simulation alone, because "you can sell it right now" is not safety. Verdicts: rug_ready / high_risk / caution / clean / unknown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNobase (default) | ethereum | bsc | polygon | arbitrum | optimism | avalanche
addressYestoken contract address

Schema Changelog

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

  1. First observed

TDQS

B3.3/5.0
Behavior4/5

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

The description discloses key behavioral traits: merging two sources, fail-closed on simulation, never returns clean on simulation alone, and lists verdicts. It does not cover authentication or rate limits, but these are not critical for a read-only assessment tool.

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 verbose and uses informal, cryptic language (e.g., 'scoring flags without that distinction is why most scanners are noise'). It front-loads with a question but lacks structured sections, making it harder to parse quickly.

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?

Despite no output schema, the description lists the five possible verdicts (rug_ready, etc.) and explains the data sources and failure modes. This provides sufficient context for a risk assessment tool with simple inputs.

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

Parameters2/5

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

Schema coverage is 100% for the two parameters (chain and address). The description does not add any additional meaning or usage details beyond what the schema provides, failing to enhance understanding of parameters.

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?

The description clearly states the tool assesses whether a token can still be rugged by checking if dangerous capabilities are fireable, and it distinguishes itself from sibling tool till_vet_meme. However, the verb is implied rather than explicit, and the wording is convoluted.

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

Usage Guidelines3/5

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

The description explains the behavior (merges two sources, fail-closed) but does not provide explicit guidance on when to use this tool versus alternatives. Usage is implied through the context of rug risk assessment.

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