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Cortex-MCP

Cortex-MCP

by codesphere-u
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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memory_verify_integrity

Verify SHA-256 hashes for all memory episodes and facts, then compute the knowledge graph’s Merkle digest to confirm stored data integrity.

Instructions

Verify cryptographic SHA-256 hashes of all episodes and facts and compute the graph Merkle digest.

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": "memory_verify_integrity"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; it does disclose the mechanism (SHA-256) and full scope ('all episodes and facts'), which implies a read-only audit rather than a mutation. It does not state whether a mismatch triggers repair or just reporting, nor whether the operation is expensive over a large store, leaving the mutation/safety profile to inference.

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?

A single front-loaded sentence naming the algorithm, the scope, and the derived output, with no filler or redundant restatement of the tool name.

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 exists, yet the description never says what a verification result looks like — expected vs. actual digest, per-episode failures, or a pass/fail flag — which is the key thing an agent needs to interpret the response. Behavior on mismatch and cost over large stores are also unaddressed, though the zero-parameter surface keeps the gap modest.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is no parameter semantics to explain and the baseline of 4 applies. The description correctly implies an unfiltered whole-store scan, consistent with an empty input 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?

The description states a specific verb and resource ('verify cryptographic SHA-256 hashes of all episodes and facts') plus a second concrete action ('compute the graph Merkle digest'). Nothing in the sibling list does integrity verification, so an agent can distinguish this tool without opening its schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to run this check — after ingestion, before trust-sensitive reads, or on a schedule — and no conditions under which an agent should prefer it over cortex_audit_contradictions or any other consistency check. Usage is only inferable from the word 'verify'.

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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