Skip to main content
Glama
mutexa-labs

@mutexa/mcp

Official
by mutexa-labs

Linkability score

linkability_score
Read-onlyIdempotent

Scores how easily a set of slices can be clustered by an observer (0-100) and lists point-adding factors with suggested fixes to reduce linkability.

Instructions

How easily a set of slices could be clustered by an observer, 0 (hard to link) to 100 (easy), with every factor that added points and its suggested fix: slice count, size spread, leverage spread, timing jitter, fresh accounts, private funding and slices above your alert threshold. A heuristic documented in the linkability spec, not a statistical guarantee.

Input Schema

NameRequiredDescriptionDefault
jitterYesTiming spread of the openings
slicesYesNotional per slice in USD
leveragesYesLeverage per slice
freshAccountsYesNo account was used before this position
alertThresholdYesYour alert threshold in USD
privateFundingYesNo slice was funded from a wallet visible to the others

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive, non-open-world behavior. The description adds meaningful context that the score is a heuristic rather than a statistical guarantee and that output includes contributing factors and suggested fixes.

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?

Front-loads the score, range, and output content before the caveat. It is appropriately compact, though the long factor list makes the single sentence dense.

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?

With no output schema, the description explains the score range, contributing factors, suggested fixes, and the non-guarantee caveat. The input schema fully covers parameter semantics, so the remaining gap is mainly exact output formatting.

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 description coverage is 100%, so all six parameters are already documented. The description reinforces their meaning as risk factors, including slices above the alert threshold, but does not add syntax or format details beyond the schema.

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?

States a specific computed metric, its 0-100 direction, and the factors it evaluates. It is clearly distinct from the market, position, and planning siblings without needing to name them.

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?

Implies the tool is used to assess how linkable a set of slices is, but it gives no explicit when-to-use, when-not-to-use, or alternative tool guidance. The heuristic caveat adds context but not usage routing.

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