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Hardik-Singh

Invariance MCP

Official
by Hardik-Singh

invariance_memory_read

Read-only

Log an agent's memory read against a subject, creating an auditable access event that flags stale or unsupported beliefs for divergence detection.

Instructions

Record a memory read by an agent against a subject (customer/account/policy/...) and return the current MemoryRecord (if any). Use this whenever an agent consults a remembered belief — it produces an auditable MemoryAccess event tying that belief to a node in the run, which the divergence detectors use to flag stale or unsupported memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesBelief key, e.g. "preferred_contact_channel" or "tier".
run_idNoRun to attach the access event to. Falls back to the server-side request context if omitted.
node_idNoNode within the run that performed the read. Falls back to request context.
used_forYesFree-text purpose for the read (used by divergence reasoning). Example: "select-channel".
subject_idYesID of the subject (e.g. customer ID, policy ID).
subject_typeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations provide readOnlyHint=true and openWorldHint=true, but the description adds critical context: it produces an auditable MemoryAccess event, which is a side effect beyond the read. This goes beyond the annotations and clarifies the behavioral contract. No contradiction with annotations since readOnlyHint likely refers to the memory store itself, not the event log.

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?

Two concise sentences, front-loaded with the action and return, followed by usage context. No fluff or redundancy. Every sentence adds value.

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 a tool with 6 parameters and no output schema, the description covers the purpose, usage trigger, and side effects. It does not describe the return format (MemoryRecord) in detail, but that is not required without an output schema. The mention of divergence detectors helps an agent understand the broader context. Overall sufficient for correct invocation.

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 high (83%) with all parameters described except subject_type which has an enum. The description does not add significant extra meaning beyond the schema; it merely echoes the purpose of used_for (divergence reasoning). Baseline 3 is appropriate as the schema carries the parameter semantics.

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 verb 'Record' and the resource 'memory read' against a subject, and explains it returns the current MemoryRecord. It also differentiates its purpose (auditable event for divergence detection) from other memory tools like memory_write, making it distinguishable without ambiguity.

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?

Explicitly states 'Use this whenever an agent consults a remembered belief' and explains the reasoning (auditable event for divergence detectors). It does not explicitly name alternatives or exclusion conditions, but the directive is clear and contextually sufficient given no other read tool exists among 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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