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/pealmeida/anymodel-plugin/statusgit clone --depth 1 https://github.com/pealmeida/anymodel-pluginWhat 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 | $0.00010 | $0.00174 |
| Opus 5 | $0.00005 | $0.00087 |
| Sonnet 5 | $0.00002 | $0.00035 |
| Haiku 4.5 | $0.00001 | $0.00017 |
Grade A, and why
status scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
80% identical to status — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
!node "${CLAUDE_PLUGIN_ROOT}/scripts/companion.mjs" status "$ARGUMENTS"
If the user did not pass a job ID:
- Render the command output as a single Markdown table for the current and past runs in this session.
- Keep it compact. Do not include progress blocks or extra prose outside the table.
- Preserve the actionable fields from the command output, including job ID, kind, status, phase, elapsed or duration, summary, and follow-up commands.
If the user did pass a job ID:
- Present the full command output to the user.
- Do not summarize or condense it.
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.
- yesterday First seen · 17 lines · 10 tokens per session scan A f047b893f543
status is a command published in the GitHub repository pealmeida/anymodel-plugin (0 stars, last pushed 24d ago), licensed Apache-2.0. It adds 10 tokens to every session and 174 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 80% identical to status, differing in 5 lines, and is treated as a copy.
Other commands, from other repositories
step-research
Always research before proposing a fix. The Untether bug you're chasing is often a known upstream engine quirk, a previously-fixed regression, or a documented config gotcha.
/release
Release a new version — updates CHANGELOG, pyproject.toml, creates git tag, and pushes.
warden-cost
Dollar accounting — what does each active rule actually save, in money? Translates the token-measured verdict into dollars using a price table and the agent's own token-type mix, with a per-session net and a break-even. Read-only; spends no tokens.
setup-team
Set up River Review in the current project: create .river/rules.md, confirm plugin install, and check integration mode.
checkpoint
Works for you. Go outside and live. — AI orchestrator that auto-routes tasks to the cheapest model that solves them. 70% run free on local models. Self-auditing, self-improving, zero prompting skill needed. Built with vibe coding by a finance student. Your models, your data.
weekly-review
Works for you. Go outside and live. — AI orchestrator that auto-routes tasks to the cheapest model that solves them. 70% run free on local models. Self-auditing, self-improving, zero prompting skill needed. Built with vibe coding by a finance student. Your models, your data.