prompt

An issue-planning assistant that assesses GitHub issues, estimates their complexity, recommends an AI model tier, and prepares a tailored work prompt.

In plain words
What is it for?
Use it to plan individual issues or batches of issues before coding and to generate copy-ready prompts with relevant context.
Why use it?
It helps match the amount of AI effort to the task, reducing both under-resourced work and unnecessary use of the most costly model tier.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/auerbachb/claude-code-config/prompt
Any agent
npx skills add auerbachb/claude-code-config --skill prompt
Clone the repo
git clone --depth 1 https://github.com/auerbachb/claude-code-config

Made for: Claude Code, Codex.

Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 10,949 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. Scan, not verified.
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 $0.00083 $0.10949
Opus 5 $0.00042 $0.05475
Sonnet 5 $0.00017 $0.02190
Haiku 4.5 $0.00008 $0.01095

Measured 2d ago against content hash e9d6fd6aacde, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

prompt scanned grade B with 1 finding 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.

Asks the agent to reveal its instructionsmediumSystem prompt leakage

Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.

- Store the CR plan content verbatim for inclusion in the output prompt
.claude/skills/prompt/SKILL.md · 523 lines

How it starts

The opening of the file, as written. The whole thing — 523 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Analyze one or more GitHub issues, classify complexity, and produce a copy-paste-ready prompt with a model recommendation. The goal is quality-conservative right-sizing — never under-resource a task, but don't waste Opus tokens on a typo fix.

Model Lineup & Effort Levels

The fleet is Fable, Opus, Sonnet, Haiku — the same four families named in CLAUDE.md, .claude/rules/subagent-orchestration.md "Model Selection", and .claude/agents/README.md. In the Claude Code picker, Opus is the default.

Always name the family, never the version (#791). A bare family name means the current non-legacy model of that family, so it never goes stale — earlier generations still listed in the picker are Legacy and are never recommended. The bare aliases used elsewhere (agent frontmatter, spawn sites) resolve the same way: opus, sonnet, haiku, and fable each resolve to the newest non-legacy model of that family. Write an explicit model ID (e.g. claude-opus-5) only where a tool literally consumes the string. Full rule and its scope: .claude/agents/README.md "Model naming".

The picker's second control is effort, and this skill recommends one on every issue. Use the picker's own labels — Low, Medium, High, Extra, Max — because a recommendation the user cannot map onto the control in front of them is one they ignore. This is the one place the label↔token mapping is taught, for the cases where something downstream consumes the raw token: Low (low), Medium (medium), High (high), Extra (xhigh), Max (max). Everywhere else, and in every recommendation this skill emits, the label alone is the value.

Ultra code (ultracode) is not a step on that ladder — it is a session-level orchestration mode, opted into for the whole session rather than set per turn (the per-call effort enum stops at max). Name it only as a step-up note alongside a real level, never as the recommended level itself.

The internal Heavy/Standard/Light tier vocabulary and decision tree are unchanged; each tier maps to a recommended effort in the output: Heavy → Extra, Standard → High, Light → Low. Users may adjust within a tier's range — a Heavy task with correctness-critical work steps up to Max; a Heavy task needing multi-agent orchestration steps up to Ultra code; a borderline Standard task steps up to Extra or down to Medium. Model choice has its own step-up: the hardest long-horizon / orchestration work can move from Opus up to Fable (see Heavy, below).

Fast mode: the picker has a Fast mode toggle (also /fast) that gives Claude Opus faster output — it speeds output without downgrading to a smaller model. It is offered on Opus; it is not offered for Sonnet, Haiku, or Fable, so it never pairs with a Light-tier recommendation. /prompt does NOT accept a --fast flag and does not factor Fast mode into recommendations — it is a user-toggled picker option. A --fast flag is a possible follow-up, not part of this skill.

Separately from Fast mode: for Light-tier work, Haiku is a valid cheaper alternative to Sonnet; the output notes this on Light-tier recommendations.

MANDATORY OUTPUT FORMAT: Every per-issue prompt block printed to the transcript MUST open and close with ~~~ tilde fences. NEVER use backtick fences as the outer prompt-block delimiter. This governs fallback mode and print-on-demand replay — the two paths that print a block. In chip mode the prompt rides inside the chip rather than being printed, so it needs no fence; its content is otherwise identical.

Per-block model and effort labels (mandatory): The **Model:** line is the first content inside each tilde-fenced block (immediately after the opening ~~~), immediately followed by the **Effort:** line — no blank line between the two:

**Model:** {MODEL} — {REASON}
**Effort:** {LEVEL} — {REASON}

{MODEL} is the bare family name for that issue's issue_tier (from Step 5 — not the batch tier) and {LEVEL} is that tier's picker label. Each {REASON} is a concise task-type phrase of at most 10 words derived from that issue's signals (dominant drivers such as rules/CLAUDE.md, orchestration, file count, AC count, skills, dependencies, or scope keywords). Both labels must be inside the tilde fence so a pasted block is self-explanatory without surrounding prose. In chip mode the same two lines MUST open the chip's prompt text and appear in the visible short summary — chips preset neither picker control, so the user needs both before clicking and the spawned session needs them after.

Read the full file on GitHub · 523 lines

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. 2d ago First seen · 523 lines · 83 tokens per session scan B e9d6fd6aacde

Subscribe to this mod's changes

prompt is a skill published in the GitHub repository auerbachb/claude-code-config (5 stars, last pushed 3d ago), licensed MIT. It adds 83 tokens to every session and 10,949 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (asks the agent to reveal its instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.