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engram

engram

by TushaeBXN
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

engram_audit

Audit persistent AI memory for health issues and return a JSON summary of found problems. Enable the fix flag to auto-resolve safe issues.

Instructions

Run a memory health audit. Returns JSON summary of issues found.

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": "engram_audit"
  }
}

Input Schema

NameRequiredDescriptionDefault
fixNoAuto-resolve safe issues.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.7.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It never discloses that passing fix=true mutates state by auto-resolving issues, nor what 'safe issues' means, whether fixes are reversible, or what permissions are required. This hides the tool's only write path.

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?

Two short, front-loaded sentences with essentially no waste; the return-format note is mildly useful given there is no output schema. It could be slightly richer without losing concision.

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?

For a one-parameter tool with no output schema, the description is minimally adequate: it names the return type (JSON summary) and the action. However, it omits what the audit covers and the mutating effect of fix=true, which an agent needs to call it safely.

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 100%, so the single 'fix' parameter and its default are already fully documented in the schema. The description adds no additional meaning about the parameter's effects, so the baseline 3 applies.

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?

The description states a specific verb+resource ('Run a memory health audit') and no sibling duplicates an audit function, so an agent can identify it distinctly. It stops short of naming how it differs from diagnostic siblings like engram_status or engram_replay.

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 the audit, how often, or when to prefer it over engram_status. The meaning of the fix option (when to auto-resolve vs. just inspect) is never explained, leaving selection entirely to inference.

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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