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/arielaizn/grok-plugin-cc/askgit clone --depth 1 https://github.com/arielaizn/grok-plugin-ccWrote 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/arielaizn/grok-plugin-cc/ask)<a href="https://agentmods.dev/commands/arielaizn/grok-plugin-cc/ask"><img src="https://agentmods.dev/badge/commands/arielaizn/grok-plugin-cc/ask.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 | $0.00010 | $0.00360 |
| Opus 5 | $0.00005 | $0.00180 |
| Sonnet 5 | $0.00002 | $0.00072 |
| Haiku 4.5 | $0.00001 | $0.00036 |
Grade A, and why
ask 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.
What it actually says
Delegate a task to Grok running headlessly in this workspace, and return what it says.
Raw slash-command arguments:
$ARGUMENTS
Core constraint:
- Grok is read-only unless the user passes
--write. Do not add--writeon their behalf. - Return Grok's answer as its own output. Do not merge it into your own reasoning as if you had worked it out, and do not silently act on its conclusions — the user asked for a second opinion, not a hand-off.
Argument handling:
- Pass the prompt through unchanged.
--effort highis worth suggesting for genuinely hard analysis; it costs more and takes longer.
Execution — foreground for a focused question:
node "${CLAUDE_PLUGIN_ROOT}/scripts/grok-companion.mjs" ask $ARGUMENTS
Background for anything that will sweep a codebase:
Bash({
command: `node "${CLAUDE_PLUGIN_ROOT}/scripts/grok-companion.mjs" ask $ARGUMENTS`,
description: "Grok delegation",
run_in_background: true
})
Output rules:
- Present Grok's answer, attributed to Grok.
- If you disagree with it, say so plainly and give your reason. Do not present a claim you believe is wrong without flagging it, and do not defer to it just because it came from another model.
- If the run failed, relay the error rather than guessing at what Grok would have said.
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 · 43 lines · 10 tokens per session scan A f6c1e9b43058
ask is a command published in the GitHub repository arielaizn/grok-plugin-cc (6 stars, last pushed 21d ago), licensed MIT. It adds 10 tokens to every session and 360 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
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.