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/choosegit 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 | $0.00015 | $0.00793 |
| Opus 5 | $0.00008 | $0.00396 |
| Sonnet 5 | $0.00003 | $0.00159 |
| Haiku 4.5 | $0.00002 | $0.00079 |
Grade A, and why
choose 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.
What it actually says
Guide the user through a semantic AnyModel chain, then dispatch to the existing runtime. This command is a selector only; do not implement delegation or review logic here.
Raw user request:
$ARGUMENTS
Semantic chain:
-
Determine the action.
- If the request clearly says
delegate,execute,run,fix,implement, orsolve, choosedelegate. - If it says
review,adversarial,challenge,critique, oraudit, chooseadversarial-review. - Otherwise use
AskUserQuestiononce:Delegate taskAdversarial review
- If the request clearly says
-
Determine provider/model.
- First preserve any explicit
--model <provider/model>argument. - Also accept natural forms like
with zai/glm-5.2,using ollama/qwen3-coder, oron opencode-go/kimi. - If an exact
<provider>/<model>is not present, run:node "${CLAUDE_PLUGIN_ROOT}/scripts/companion.mjs" models --json - Parse the JSON. Ignore providers with
ok: falseor an emptymodelslist. - If no usable provider/model is available, stop and return the models output verbatim, then tell the user to run
/anymodel:setup. - If the user named a provider but not a model, ask them to choose one reachable model for that provider.
- If the user named neither provider nor model, ask them to choose from the most useful reachable options. Prefer showing up to three concrete choices as
<provider>/<model>, using the provider/model names exactly as returned bymodels --json.
- First preserve any explicit
-
Determine the engine.
- Preserve any explicit
--engine <id>. - If omitted, do not ask. Let the companion runtime use its configured default engine.
- Preserve any explicit
-
Determine the work text.
- For
delegate, require a task. If the request does not include one after removing action/provider/model selection words, ask what the selected model should investigate, solve, or implement. - For
adversarial-review, focus text is optional. Preserve any provided focus text exactly.
- For
-
Dispatch.
- Build a final argument string from the original flags that are still relevant, the selected
--model <provider/model>, and the task/focus text. - Preserve
--engine,--bridge,--write,--base,--scope,--wait,--background,--resume, and--freshwhen present. - Do not include selector-only words like
delegate with,review using, orchoose.
- Build a final argument string from the original flags that are still relevant, the selected
Delegate dispatch:
- Invoke the
anymodel:anymodel-runnersubagent via theAgenttool (subagent_type: "anymodel:anymodel-runner"), forwarding the final request as if the user had called/anymodel:delegate. - The subagent must make exactly one Bash call to:
node "${CLAUDE_PLUGIN_ROOT}/scripts/companion.mjs" delegate <final arguments> - Return the companion stdout verbatim.
Adversarial review dispatch:
- Run:
node "${CLAUDE_PLUGIN_ROOT}/scripts/companion.mjs" adversarial-review <final arguments> - Return stdout verbatim. Do not summarize, fix, or add commentary after the review.
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.
- 2d ago First seen · 63 lines · 15 tokens per session scan A 25b758c17146
choose is a command published in the GitHub repository pealmeida/anymodel-plugin (0 stars, last pushed 24d ago), licensed Apache-2.0. It adds 15 tokens to every session and 793 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
/commit-push
Commit and push all changes from this chat session using Conventional Commits.
/release
Release a new version — updates CHANGELOG, pyproject.toml, creates git tag, and pushes.
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.
hybrid-auto
Generate PRD from task description and enter review mode. Auto-generates user stories with priorities, dependencies, and acceptance criteria for parallel execution. Usage: /plan-cascade:hybrid-auto [--flow ] [--tdd ] [--confirm] [--no-confirm] [--spec ] [--first-principles] [--max-questions N] [--agent ]…
hybrid-worktree
Start a new task in an isolated Git worktree with Hybrid Ralph PRD mode. Creates worktree, branch, loads existing PRD or auto-generates from description. Usage: /plan-cascade:hybrid-worktree [--flow ] [--tdd ] [--confirm] [--no-confirm] [--spec ] [--first-principles] [--max-questions N] [--agent ] [design-doc-path].