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biii

by io.github.philpof102-svg

till_open_approvals

WHICH DOORS INTO THIS WALLET ARE STILL OPEN? An ERC-20 approval is a standing permission to move your tokens without asking again, and it is the most common drain vector that does NOT require the private key: you approved a contract once for an unlimited amount and forgot. Wallets do not surface these, so almost nobody knows what they have granted. The load-bearing discipline: an Approval EVENT IS NOT THE CURRENT STATE — a later approval of zero revokes an earlier one silently, so the log is used only to find candidate (token, spender) pairs and every one is then confirmed by calling allowance() on the chain right now. Reports three outcomes, never two: live, confirmed-revoked, and COULD-NOT-CHECK. The first draft collapsed the last two and reported forty closed doors having verified nine — an unanswered call is not a closed door. Read-only: it tells you what to revoke and where, and can never revoke or sign anything itself.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNobase (default) | ethereum
ownerYesthe wallet address to audit
fromBlockNooptional: scan from this block (default 0)

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations provided, the description fully discloses behavioral traits: it is read-only, confirms each candidate via allowance(), and reports three distinct outcomes (live, confirmed-revoked, could-not-check). It explicitly states it 'can never revoke or sign anything itself', ensuring transparency.

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 verbose but well-structured: it opens with a headline, explains the problem, methodology, output categories, and safety. Every sentence earns its place, though slight trimming could improve conciseness.

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?

Given the lack of annotations and output schema, the description covers key behaviors and output categories. However, it does not specify the exact return format (e.g., JSON structure), which would help an AI agent fully understand the response. Still, it is largely complete for the tool's complexity.

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 coverage is 100%, so the baseline is 3. The description does not add new information about parameters beyond what the schema already provides; it focuses on behavior instead. No deductions or additions needed.

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 defines the tool's purpose: auditing open ERC-20 approvals for a wallet. It uses specific, action-oriented language ('WHICH DOORS INTO THIS WALLET ARE STILL OPEN?') and distinguishes itself from sibling tools by focusing exclusively on approvals.

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 description provides strong usage context by explaining the danger of lingering approvals and the misconception that events are current state. It implies when to use (to discover standing permissions) but does not explicitly state when not to use or list alternative tools.

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