Wicked MCP

reputation_query

Search/rank registered agents by tier, stake, reputation, or slash history. A safe, parameterized alternative to raw SQL — every filter is a typed query param, there's no query-injection surface.

Args:
    tier: Exact tier name to filter to, e.g. "gold".
    min_stake / max_stake: Active-stake bounds in USDC.
    min_reputation: Minimum reputation score.
    founding_member: True to only show founding members.
    min_slash_count: Minimum number of slash events (e.g. 1 to find agents that have ever been slashed).
    sort: Field to sort by, optionally prefixed "-" (descending, default) or "+" (ascending).
        One of stake_amount, reputation_score, slash_count, registered_at.
    limit: Max results, 1-200. Defaults to 20.

Input Schema

TableJSON Schema

Name	Required	Default
`sort`	No	-stake_amount
`tier`	No
`limit`	No
`max_stake`	No
`min_stake`	No
`min_reputation`	No
`founding_member`	No
`min_slash_count`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 2, 2026

TDQS

A3.8/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden. It usefully discloses the safety profile (parameterized, no injection surface), default sort direction, limit bounds of 1-200, and default limit of 20. It never states read-only semantics or permission requirements explicitly, and the return shape is left to the output schema.

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-loaded purpose sentence followed by a clean Args block; each line earns its place. Slightly verbose but nothing is wasted, and the ordering is logical.

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?

For an 8-param tool with zero schema coverage and an existing output schema, the description covers all inputs thoroughly. The only gap is that it does not clarify how multiple filters combine (AND vs OR) or confirm the read-only nature, but nothing essential for a correct call is missing.

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?

With 0% schema description coverage, the description fully compensates: it documents every one of the 8 params including example tier values, USDC units for stake bounds, the +/- prefix convention for sort direction with the four allowed fields, and the limit range and default.

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?

States a specific verb pair (search/rank) and resource (registered agents) plus the dimensions queried (tier, stake, reputation, slash history), so an agent knows exactly what this returns. It does not explicitly distinguish itself from the four reputation_* siblings, which is the only thing keeping it from a 5.

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?

Usage is implied by the filter list, but there is no explicit when-to-use versus reputation_statement, reputation_status, reputation_tiers, or reputation_transparency. The 'safe alternative to raw SQL' framing contrasts with a non-existent tool rather than routing the agent among real siblings.

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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