Synpareia Trust Toolkit

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evaluate_agent

Evaluate a counterparty across all configured trust tiers. Pass namespace and id to route evidence, receiving tiered results and a summary for informed decisions.

Instructions

Evaluate a counterparty across every configured tier.

Pass namespace + id to route explicitly. namespace is the platform / context ("synpareia", "moltbook", "slack", "discord", "email", ...); id is the identifier within that namespace (a DID, handle, username, or local record id).

id may also be passed as namespace_id — that is the field name remember_counterparty emits, so a Tier-1 record pipes straight into this call without renaming (round-trip audit, task #40).

Returns {tier1, tier2, tier3, tier4_available, providers_queried, providers_skipped, summary}. Every tier is a list; empty lists mean "no evidence at this tier" (never an error). An agent reads the structured result and decides how to weight each tier.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "evaluate_agent"
  }
}

Input Schema

Name	Required	Description	Default
`id`	No
`namespace`	No
`namespace_id`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.8.0Jul 14, 2026

removedInput schema / properties / identifier

Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "title": "Identifier"
-}

First observedv0.6.3Jul 6, 2026

TDQS

A4.3/5.0

Behavior3/5

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

Describes return format and interpretation (empty lists not errors), but does not explicitly state side effects or permissions. Given no annotations, it covers basic behavior but lacks depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is concise, well-structured, and front-loaded. Each sentence provides essential information without redundancy.

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?

Covers parameters, return structure, and usage intent well. Lacks mention of error conditions or prerequisites, but overall complete for a read-like evaluation tool with no required parameters.

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?

Schema has 0% coverage, but description explains each parameter in detail: namespace as platform context, id as identifier, namespace_id as shortcut from remember_counterparty. Fully compensates.

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?

Clearly states 'Evaluate a counterparty across every configured tier', with specific verb and resource. Distinguishes from siblings like 'find_evaluations' because it evaluates across all tiers.

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?

Explains how to route with namespace+id or namespace_id, and provides context for when to use each. No explicit when-not but adequate guidance.

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