maintenance

A routine-maintenance command for an AI knowledge base, a system that stores information for later search. It checks the index, backs up knowledge, updates environment details, tests search, and reviews known problems.

In plain words
What is it for?
Use it to validate or repair the knowledge index, create a backup, detect the current environment, test a search, and review gotchas.
Why use it?
It gathers recurring checks in one workflow, making it easier to spot broken search data or missing backups.

Command for Cursor

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/andiupn/andy-universal-agent-rules/maintenance
Clone the repo
git clone --depth 1 https://github.com/andiupn/andy-universal-agent-rules

Made for: Cursor.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 206 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00206
Opus 5 $0.00000 $0.00103
Sonnet 5 $0.00000 $0.00041
Haiku 4.5 $0.00000 $0.00021

Measured 2d ago against content hash dd661fba5f3b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

maintenance scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.cursor/commands/maintenance.md · 43 lines

What it actually says

Maintenance Workflow

Run routine maintenance on the AI knowledge base system.

What This Does

  1. Validates knowledge base index integrity
  2. Creates backup of current knowledge
  3. Updates environment detection
  4. Tests search functionality
  5. Reviews gotchas for relevance

Commands to Run

# 1. Validate index
python .agent/scripts/validate-index.py --report

# If errors found:
python .agent/scripts/validate-index.py --fix

# 2. Create backup
python .agent/scripts/backup-memory.py

# 3. Update environment
python .agent/scripts/detect-environment.py

# 4. Test search
python .agent/scripts/search-knowledge.py "test" --limit 3

Checklist

  • Index validated (no errors)
  • Backup created
  • Environment updated
  • Search working
  • Gotchas reviewed

Use: Type /maintenance in Cursor Chat

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 43 lines · 0 tokens per session scan A dd661fba5f3b

Subscribe to this mod's changes

maintenance is a command published in the GitHub repository andiupn/andy-universal-agent-rules (2 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 206 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.