grok-prompting

grok-prompting is a skill for Claude Code from dysfunc/ai-plugins-cc. It costs 30 tokens per session (790 once invoked), scanned A, original, Apache-2.0.

Internal instructions for writing prompts for Grok, an AI model, inside the Grok Claude Code plugin.

In plain words
What is it for?
Use them when asking Grok to plan work, research a question, diagnose a problem, or review code.
Why use it?
They help provide Grok with the code, logs, and requirements it needs when it cannot inspect files or run commands itself.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: mentions Claude Code.

Part of the grok plugin — 3 skills, 1 agent shipped together

Good fit Use them when asking Grok to plan work, research a question, diagnose…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dysfunc/ai-plugins-cc/grok-prompting
Install

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.

Any agent
npx skills add dysfunc/ai-plugins-cc --skill grok-prompting
Clone the repo
git clone --depth 1 https://github.com/dysfunc/ai-plugins-cc

Made for: Claude Code.

Or install grok, the plugin that ships this one along with the rest of its 3 skills, 1 agent.

Wrote 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.

agentmods badge for grok-prompting

README.md
[![agentmods](https://agentmods.dev/badge/skills/dysfunc/ai-plugins-cc/grok-prompting.svg)](https://agentmods.dev/skills/dysfunc/ai-plugins-cc/grok-prompting)
Your own site
<a href="https://agentmods.dev/skills/dysfunc/ai-plugins-cc/grok-prompting"><img src="https://agentmods.dev/badge/skills/dysfunc/ai-plugins-cc/grok-prompting.svg" alt="Measured on agentmods" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 790 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00030 $0.00790
Opus 5 $0.00015 $0.00395
Sonnet 5 $0.00006 $0.00158
Haiku 4.5 $0.00003 $0.00079

Measured 6d ago against content hash fc5a1f1e4cd6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

grok-prompting 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 6d 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.

plugins/grok/skills/grok-prompting/SKILL.md · 53 lines

What it actually says

Grok Prompting

Use this skill when grok:grok-rescue needs to ask Grok for help via the task runtime.

Prompt Grok like an analyst, not a collaborator with tool access. The plugin runs Grok headless via grok -p, so it cannot read files, run commands, or browse the working tree on its own. Everything Grok sees has to be in the prompt text.

Core rules:

  • Prefer one clear task per Grok run. Split unrelated asks into separate runs.
  • Tell Grok what done looks like. Do not assume it will infer the desired end state.
  • Keep prompts compact and block-structured with XML tags so the contract has stable shape.
  • Inline any relevant code, log output, or file excerpts directly in the prompt — Grok cannot fetch them.
  • Add explicit grounding rules for any task where unsupported guesses would hurt quality (review, diagnosis, postmortem analysis).
  • For follow-up requests, the plugin prepends the prior per-job transcript automatically; you only need to send the delta instruction.

Default prompt recipe:

  • <task>: the concrete job and the relevant repository or failure context (inlined).
  • <structured_output_contract> or <compact_output_contract>: exact shape, ordering, and brevity requirements.
  • <default_follow_through_policy>: what Grok should do by default instead of asking routine questions.
  • <grounding_rules>: required for review, research, or anything that could drift into unsupported claims.

When to add blocks:

  • Diagnosis or planning: add <completeness_contract> and an <observable_evidence> block listing what you've inlined.
  • Review or adversarial review: prefer the built-in /grok:review and /grok:adversarial-review commands — those carry the review contract and JSON schema. Only fall back to task when the review needs a non-standard target or shape.
  • Research or recommendation tasks: add <research_mode> and <citation_rules> (cite the inlined evidence by line reference, not URL).

Working rules:

  • Prefer explicit prompt contracts over vague nudges.
  • Use stable XML tag names so the structure is recognizable across runs.
  • Do not raise reasoning effort first. Tighten the prompt and grounding rules before escalating.
  • Ask Grok for brief, outcome-based progress updates only when the task is long-running.
  • Keep claims anchored to inlined evidence. If something is a hypothesis, say so.
  • For long-running follow-ups, lean on --resume-last so the prior transcript is reused; the plugin truncates oldest turns when the transcript exceeds the cap.

Prompt assembly checklist:

  1. Define the exact task and scope in <task>.
  2. Inline the evidence Grok needs to answer — file excerpts, log slices, error messages, schemas.
  3. Choose the smallest output contract that still makes the answer easy to use.
  4. Decide whether Grok should keep going by default or stop for missing high-risk details.
  5. Add grounding and verification tags only where the task needs them.
  6. Remove redundant instructions before sending the prompt.

Common antipatterns:

  • Asking Grok to "look at file X" — it cannot. Inline X (or a relevant slice) in the prompt instead.
  • Asking Grok to "run the tests and report" — it cannot. Run them yourself, inline the output, then ask Grok to analyze.
  • Restating the full prompt on every --resume-last turn — the prior transcript is already prepended.
  • Mixing several unrelated questions in one prompt — split them into separate task runs.
Changes

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.

  1. 6d ago First seen · 53 lines · 30 tokens per session scan A fc5a1f1e4cd6

Subscribe to this mod's changes

grok-prompting is a skill published in the GitHub repository dysfunc/ai-plugins-cc (4 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 790 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 2026-08-31.