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.
git clone --depth 1 https://github.com/yacb2/domaintomeWrote 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/yacb2/domaintome/stats)<a href="https://agentmods.dev/commands/yacb2/domaintome/stats"><img src="https://agentmods.dev/badge/commands/yacb2/domaintome/stats/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/yacb2/domaintome/stats"><img src="https://agentmods.dev/badge/commands/yacb2/domaintome/stats.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00026 | $0.00384 |
| Opus 5.5 | $0.00010 | $0.00154 |
| Sonnet 5.5 | $0.00005 | $0.00077 |
| Haiku 4.5 | $0.00003 | $0.00038 |
Grade A, and why
stats scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Report DomainTome's own usage analytics: how many MCP calls have been made against this graph, the byte volume exchanged (with a rough token estimate), and a per-tool / per-op breakdown.
Steps
-
Run
dt statsagainst the current project's DB. If$ARGUMENTScontains an ISO timestamp, pass it as--since:dt stats [--since $ARGUMENTS] -
Summarize the output in a tight block:
## DomainTome usage (<period>) - Calls: N (errors: N) - Total exchanged: X KB (~Y tokens) - Input: X KB (~Y tokens) - Output: X KB (~Y tokens) ### By tool - dt_add_node: N calls · X KB (~Y tokens) - dt_audit: N calls · X KB (~Y tokens) - ... ### By op - audit / read / create / update / delete counts. -
Honest proxy note: the CLI does not measure true tokens; the column is
bytes × 0.3, useful for relative comparisons between tools or time periods, not for billing-grade numbers. Mention this only if the user asks for precision.
When to use
- After a
/dt:sync(INIT or EXTEND mode) to see what the seed/extend pass cost. - Periodically to spot unusually hot tools.
- With
--since <yesterday>to scope to a session.
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.
- 1mo ago First seen · 50 lines · 26 tokens per session scan A a8a7fd467aae
stats is a command published in the GitHub repository yacb2/domaintome (0 stars, last pushed 1mo ago), licensed MIT. It adds 26 tokens to every session and 384 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-31.
Other commands, from other repositories
mega-approve
Approve the mega-plan and start feature execution. Creates worktrees and generates PRDs for each feature. Usage: /plan-cascade:mega-approve [--flow ] [--tdd ] [--confirm] [--no-confirm] [--spec ] [--first-principles] [--max-questions N] [--auto-prd] [--agent ] [--prd-agent ] [--impl-agent ].
auto
AI auto strategy executor. Analyzes task and automatically selects and executes the best strategy: direct execution, hybrid-auto PRD generation, hybrid-worktree isolated development, or mega-plan multi-feature orchestration.
resume
Auto-detect and resume any interrupted Plan Cascade task. Detects mega-plan, hybrid-worktree, or hybrid-auto context and routes to the appropriate resume command.
worktree
Start a new task in an isolated Git worktree for parallel multi-task development. Creates a task branch, worktree directory with planning files, and leaves the main directory untouched. Usage: /plan-cascade:worktree [task-name] [target-branch]. Example: /plan-cascade:worktree feature-login main.
mega-status
Show detailed status of mega-plan execution including feature progress and story completion. Usage: /plan-cascade:mega-status.
edit
Edit the current PRD in your default editor. Opens prd.json, validates after saving, and re-displays review. Supports adding/removing stories, changing priorities, and modifying dependencies.