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.
npx agentmods add commands/shwilliamson/automatasaurus/auto-cleargit clone --depth 1 https://github.com/shwilliamson/automatasaurusWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/shwilliamson/automatasaurus/auto-clear)<a href="https://agentmods.dev/commands/shwilliamson/automatasaurus/auto-clear"><img src="https://agentmods.dev/badge/commands/shwilliamson/automatasaurus/auto-clear.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00841 |
| Opus 5 | $0.00000 | $0.00420 |
| Sonnet 5 | $0.00000 | $0.00168 |
| Haiku 4.5 | $0.00000 | $0.00084 |
Grade A, and why
auto-clear 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Clear - Remove Generated Planning Files
Remove all generated planning and context files to start fresh.
Workflow Mode
WORKFLOW_MODE: clear
Instructions
You are the Cleanup Assistant. Your job is to:
- Find all generated planning files
- Show the user what will be removed
- Offer backup or direct deletion
- Clean up and confirm
Phase 1: Find Generated Files
Glob for all generated planning and context files:
# Discovery files
ls discovery.md discovery-*.md 2>/dev/null
# Implementation plan files
ls implementation-plan.md implementation-plan-*.md 2>/dev/null
# Design system
ls design-system.md 2>/dev/null
# Agent PROJECT.md files
ls .claude/agents/*/PROJECT.md 2>/dev/null
If no files are found, inform the user:
No generated planning files found. Nothing to clear.
Phase 2: Present Files to User
List all found files with sizes:
## Generated Planning Files Found
| File | Size |
|------|------|
| discovery.md | X KB |
| discovery-2.md | X KB |
| implementation-plan.md | X KB |
| design-system.md | X KB |
| .claude/agents/developer/PROJECT.md | X KB |
| .claude/agents/architect/PROJECT.md | X KB |
| .claude/agents/designer/PROJECT.md | X KB |
| .claude/agents/tester/PROJECT.md | X KB |
What would you like to do?
1. **Delete all** - Remove all generated files
2. **Backup then delete** - Copy to `.automatasaurus/backups/` first, then remove
3. **Cancel** - Keep everything
Phase 3: Execute Chosen Action
Option 1: Delete All
rm -f discovery.md discovery-*.md
rm -f implementation-plan.md implementation-plan-*.md
rm -f design-system.md
rm -f .claude/agents/*/PROJECT.md
Option 2: Backup Then Delete
# Create timestamped backup directory
BACKUP_DIR=".automatasaurus/backups/planning-$(date +%Y%m%d-%H%M%S)"
mkdir -p "$BACKUP_DIR"
# Copy all generated files preserving structure
cp discovery.md discovery-*.md "$BACKUP_DIR/" 2>/dev/null
cp implementation-plan.md implementation-plan-*.md "$BACKUP_DIR/" 2>/dev/null
cp design-system.md "$BACKUP_DIR/" 2>/dev/null
mkdir -p "$BACKUP_DIR/agents"
for agent_dir in .claude/agents/*/; do
agent_name=$(basename "$agent_dir")
if [ -f "$agent_dir/PROJECT.md" ]; then
mkdir -p "$BACKUP_DIR/agents/$agent_name"
cp "$agent_dir/PROJECT.md" "$BACKUP_DIR/agents/$agent_name/"
fi
done
# Then delete
rm -f discovery.md discovery-*.md
rm -f implementation-plan.md implementation-plan-*.md
rm -f design-system.md
rm -f .claude/agents/*/PROJECT.md
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.
- 4d ago First seen · 150 lines · 0 tokens per session scan A 9396d01b657c
auto-clear is a command published in the GitHub repository shwilliamson/automatasaurus (5 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 841 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.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
session-end
I'll summarize this coding session and update the memory system with our accomplishments.
memory-store
Store an insight, decision, or pattern to memory.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.