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/taoidle/plan-cascade/mega-resumegit clone --depth 1 https://github.com/Taoidle/plan-cascadeWhat 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 | $0.00034 | $0.04081 |
| Opus 5 | $0.00017 | $0.02041 |
| Sonnet 5 | $0.00007 | $0.00816 |
| Haiku 4.5 | $0.00003 | $0.00408 |
Grade A, and why
mega-resume 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 3d 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 — 547 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resume Interrupted Mega Plan
Resume execution of an interrupted mega-plan by detecting the current state from existing files.
Path Storage Modes
This command works with both new and legacy path storage modes:
New Mode (Default)
Files are stored in user data directory:
- Windows:
%APPDATA%/plan-cascade/<project-id>/ - Unix/macOS:
~/.plan-cascade/<project-id>/
File locations:
mega-plan.json:<user-dir>/mega-plan.json.mega-status.json:<user-dir>/.state/.mega-status.json- Worktrees:
<user-dir>/.worktree/<feature-name>/
Legacy Mode
All files in project root:
mega-plan.json:<project-root>/mega-plan.json.mega-status.json:<project-root>/.mega-status.json- Worktrees:
<project-root>/.worktree/<feature-name>/
The command auto-detects which mode is active and scans the appropriate directories.
Tool Usage Policy (CRITICAL)
To avoid command confirmation prompts during automatic execution:
-
Use Read tool for file reading - NEVER use
catvia Bash- ✅
Read("mega-plan.json"),Read(".mega-status.json"),Read(".worktree/x/progress.txt") - ❌
Bash("cat mega-plan.json")
- ✅
-
Use Glob tool for finding files - NEVER use
lsorfindvia Bash- ✅
Glob(".worktree/*/prd.json") - ❌
Bash("ls .worktree/")
- ✅
-
Use Grep tool for content search - NEVER use
grepvia Bash- ✅
Grep("[PRD_COMPLETE]", path=".worktree/x/progress.txt") - ❌
Bash("grep '[PRD_COMPLETE]' ...")
- ✅
-
Only use Bash for actual system commands:
- Git operations:
git worktree add,git merge - Directory creation:
mkdir -p - File writing:
echo "..." >> progress.txt
- Git operations:
Compatibility: Works with both old-style (pre-4.1.1) and new-style mega-plan executions.
Arguments
--auto-prd: Continue in fully automatic mode (no manual intervention)
Step 1: Verify Mega Plan Exists
# Get mega-plan path from PathResolver
MEGA_PLAN_PATH=$(uv run python -c "from plan_cascade.state.path_resolver import PathResolver; from pathlib import Path; print(PathResolver(Path.cwd()).get_mega_plan_path())" 2>/dev/null || echo "mega-plan.json")
if [ ! -f "$MEGA_PLAN_PATH" ]; then
echo "============================================"
echo "ERROR: No mega-plan.json found"
echo "============================================"
echo "Searched at: $MEGA_PLAN_PATH"
echo "Nothing to resume."
echo "Use /plan-cascade:mega-plan <description> to create a new plan."
exit 1
fi
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.
- 3d ago First seen · 547 lines · 34 tokens per session scan A 8a802f55b0d2
mega-resume is a command published in the GitHub repository Taoidle/plan-cascade (131 stars, last pushed 5mo ago), licensed MIT. It adds 34 tokens to every session and 4,081 once invoked, about $0.0002 per session on Opus 5. 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 2026-08-30.
Other commands, from other repositories
/release
Release a new version — updates CHANGELOG, pyproject.toml, creates git tag, and pushes.
delegate
Delegate a task to any engine and model through the anymodel-runner subagent.
choose
Pick an AnyModel action, provider, and model through an interactive semantic chain.
delegate-with
Delegate through an interactive provider and model selection chain.
review-with
Run an adversarial review through an interactive provider and model selection chain.
setup
Check local engine and provider setup, and optionally toggle the stop-time review gate.