ai-dememory

by GonzaloTorreras

Overview Schema Source Related Servers Discussions Admin

Python

Local

Recall Fixture Status

memory.recall_fixture_status

Read-only

Check recall fixture provenance and reviewed-promotion freshness with a configurable age limit.

Instructions

Report recall fixture provenance and reviewed-promotion freshness.

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.recall_fixture_status"
  }
}

Input Schema

Name	Required	Description	Default
`max_age_days`	No

Output Schema

Name	Required	Description	Default
`stale`	Yes
`status`	Yes
`next_action`	Yes
`max_age_days`	Yes
`fixtures_path`	Yes
`seed_fixtures`	Yes
`total_fixtures`	Yes
`latest_created_at`	No
`latest_reviewed_at`	No
`reviewed_promotions`	Yes
`days_since_latest_review`	No
`needs_reviewed_promotion`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Jul 9, 2026

TDQS

B3.1/5.0

Behavior3/5

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

Annotations declare readOnlyHint=true, so the tool is safe. The description adds context that it reports provenance and freshness, which are non-obvious behavioral aspects. However, it does not detail what happens with different inputs or edge cases.

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?

Single sentence, no redundancy. Every word contributes to defining the tool's purpose.

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?

Given a single optional parameter and an output schema (not detailed), the description covers the core function but omits explanation of key terms ('provenance', 'reviewed-promotion freshness') and the parameter's role. Adequate for domain insiders but not fully complete.

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

Parameters2/5

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

The sole parameter max_age_days has no description in the schema (0% coverage). The tool description does not explicitly link 'freshness' to this parameter, leaving the agent to infer the connection. This is insufficient for a parameter with no schema documentation.

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 it reports 'recall fixture provenance and reviewed-promotion freshness', which clarifies the subject and metrics. While jargon-heavy, it distinguishes from sibling tools like 'recall_review_packet' by focusing on fixture status.

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?

No guidance on when to use this tool versus alternatives (e.g., other recall tools). The description does not mention conditions or exclusions.

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

Deploy Server