mind-dump

mind-dump is a skill for Claude Code from spinningrachel/career-engine. It costs 26 tokens per session (884 once invoked), scanned A, original, MIT.

An interview method for helping someone explain ideas they already have but have not fully expressed. It uses focused questions to turn broad thoughts into specific claims.

In plain words
What is it for?
It is for drawing out the exact angle, audience, and reason behind ideas before they are written or organised.
Why use it?
It avoids losing useful details or settling for vague topics during an idea-gathering conversation.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the career-engine plugin — 29 skills, 16 agents, 1 hook shipped together

Good fit It is for drawing out the exact angle, audience, and reason behind ideas before they are written or organised.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/spinningrachel/career-engine/mind-dump
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 spinningrachel/career-engine --skill mind-dump
Clone the repo
git clone --depth 1 https://github.com/spinningrachel/career-engine

Made for: Claude Code.

Or install career-engine, the plugin that ships this one along with the rest of its 29 skills, 16 agents, 1 hook.

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 mind-dump

README.md
[![agentmods](https://agentmods.dev/badge/skills/spinningrachel/career-engine/mind-dump.svg)](https://agentmods.dev/skills/spinningrachel/career-engine/mind-dump)
Your own site
<a href="https://agentmods.dev/skills/spinningrachel/career-engine/mind-dump"><img src="https://agentmods.dev/badge/skills/spinningrachel/career-engine/mind-dump.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 884 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 $0.00026 $0.00884
Opus 5 $0.00013 $0.00442
Sonnet 5 $0.00005 $0.00177
Haiku 4.5 $0.00003 $0.00088

Measured 8d ago against content hash 289a0da81946, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

mind-dump 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 8d 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.

skills/mind-dump/SKILL.md · 82 lines

How it starts

The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Mind-Dump Interview Methodology

Philosophy

A mind-dump is not a brainstorm. The user already has thoughts — they just haven't been said out loud yet. Your job is to create the conditions for them to surface completely. Generic prompts ("what's on your mind?") produce generic answers. You need to pull the specific out of the general.

The three failure modes to avoid:

  1. Accepting the first answer. "I want to write about documentation" is not an idea — it's a category. Keep probing until there's a specific claim.
  2. Moving on too fast. Users drop half-ideas while pivoting to the next thought. The dropped idea is often the most interesting one.
  3. Letting vague language stand. "Something about collaboration" needs a specific what, who, and why before it can be captured.

Entry

Open with: "What's been on your mind lately that you haven't had a chance to articulate yet?" or "What do you want to get out of your head today?"

Accept whatever comes — one thing, many things, a rambling wall of text. Do not reorder or summarise yet. Just listen.

Probing Rules

For each idea mentioned, probe in this order until all three are clear:

  1. The specific angle — What exactly is the claim or observation? Not the topic, the take. "Documentation" is a topic. "Most documentation fails because it's written for the author, not the reader" is an angle.

  2. The evidence or experience — What specific thing happened, what did you see, what's the proof? Named companies, real timelines, actual outcomes. If the user can't name any evidence, the idea needs more development before it's ready to capture — note that explicitly.

  3. The audience or application — Who is this for? What would they do differently after reading/hearing this?

Catch-and-Return Protocol

When you notice the user dropped an idea mid-sentence or pivoted away before finishing:

  • Wait until they complete their current thought.
  • Then: "You mentioned [X] earlier — let's come back to that. What's the specific angle there?"

Read the full file on GitHub · 82 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. 8d ago First seen · 82 lines · 26 tokens per session scan A 289a0da81946

Subscribe to this mod's changes

mind-dump is a skill published in the GitHub repository spinningrachel/career-engine (4 stars, last pushed 26d ago), licensed MIT. It adds 26 tokens to every session and 884 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens