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Glama

biii

by io.github.philpof102-svg

till_recovery_offer

THE SECOND THEFT: judge an approach offering to recover already-stolen funds. Every other tool here tries to stop the first loss; this exists because the first loss is what makes a person findable, and a drained wallet is a lead with a market for it. Answerable with certainty rather than a score, because the ask itself is the tell: recovery happens through the thief returning funds, or a court, exchange, or issuer freezing and reassigning them — none of which require anything from the victim's wallet. So a recovery needing your signature or an upfront fee is not merely suspect, it is structurally impossible as described, no matter how credible the person sounds or how accurately they recite your loss (the theft is public — anyone can read it back to you). Also reads the chain for the harvesting shape: many unrelated senders paying one address that returns nothing. NEVER returns "safe".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNobase (default) | ethereum | polygon | arbitrum | optimism
addressNothe address you were asked to pay or interact with (optional — its absence is not reassurance)
asksToInstallNowere you asked to download or run anything?
asksForSeedOrKeyNowere you asked for a seed phrase, private key or keystore?
asksForSignatureNowere you asked to sign a message or transaction?
asksForUpfrontPaymentNowere you asked to pay a fee before delivery?

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior5/5

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

With no annotations, the description fully discloses behavior: it never returns 'safe', reads the chain for harvesting patterns, and explains why certain recovery claims are structurally impossible. It provides clear output logic.

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 poetic, lacking conciseness. Important information is buried in a long narrative, making it less efficient for AI parsing.

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?

No output schema; description partially explains output (certain answer, never 'safe', chain reading) but lacks explicit return format or value details. Adequate but could be more complete for a 6-parameter tool.

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 baseline is 3. Description adds minimal extra meaning beyond parameter descriptions; it does not elaborate on how to use parameters effectively.

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 judges recovery offers for stolen funds, contrasting with siblings that handle first-time theft. The verb 'judge' and resource 'approach offering to recover already-stolen funds' are specific and differentiated.

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 context on when to use (for recovery offers) and explains the tool's certain answer. However, it does not explicitly state when not to use or mention 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