Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsCommunityBlog
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Authors
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

ProTermsPrivacyRefunds
Back to skills

How

ASecurity

Use for runtime, ownership, layering, code-walkthrough, and placement questions.

2 stars
0 votes
0 copies
0 views
Added 9/23/2026
ai-agentsgo

Works with

cursor

Security Analysis

A100/100

Scanned 9/23/2026

Install to Claude Code

$npx -y skills add jaydubya818/MissionControl --skill how --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of How?

Add the live security badge to your README — it updates automatically with every re-scan.

Security grade badge for How
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/jaydubya818-how/badge)](https://www.skillsdirectory.com/skills/jaydubya818-how)

More formats (shields.io, HTML) on the badges page.

Download with Pro
Files
SKILL.md
---
name: how
description: "Use for runtime, ownership, layering, code-walkthrough, and placement questions."
license: MIT
metadata:
  author: jstack-maintainers
  source: michael-denyer/pstack-claude
  source-version: "0.9.30"
  source-commit: 45f768349a6d7d7e71509fee3f5bccfad54b3bad
  owner: software-factory
  risk: low
  capabilities: jstack,engineering-research
---

# How

On Codex, Cursor, or another non-Claude runtime, read the [runtime mapping](../poteto-mode/references/harness-tools.md), including its per-skill notes, before following this skill.

Explore the codebase to answer "how does X work?" questions. Produce architectural explanations at the level of a senior engineer onboarding onto a subsystem, enough to build a working mental model, not so much that it reads like annotated source code.

## Step 1. Assess Complexity

If the scope is ambiguous, state your interpretation and explore. The user can redirect.

- **Simple** (a single module, a small utility, a narrow question such as "how does function X work"): no explorers. One explainer explores and explains in a single pass. Go to Step 2b.
- **Complex** (a subsystem spanning multiple files or services, a cross-cutting feature, a full architectural overview): spawn parallel explorers first, then hand off to the explainer. Go to Step 2a.

When in doubt, take the simple path.

## Step 2a. Explore (complex questions only)

Decompose the question into 2 to 4 exploration angles, each a distinct slice of the subsystem. Spawn all explorers in a single message:

- `subagent_type`: `general-purpose`
- `model`: your configured how-explorer model (default in [Models](#models))
- `readonly`: `true`

Each explorer gets the prompt in `references/explorer-prompt.md` with its angle filled in. Then go to Step 3.

## Step 2b. Direct Explain (simple questions)

Spawn one Task subagent that explores and explains in one pass:

- `subagent_type`: `general-purpose`
- `model`: your configured how-explainer model (default in [Models](#models))
- `readonly`: `true`

Build its prompt from `references/explainer-prompt.md` without the explorer-findings section. Go to Step 4.

## Step 3. Synthesize (complex questions only)

Once all explorers have returned, spawn one Task subagent to synthesize their findings into one explanation:

- `subagent_type`: `general-purpose`
- `model`: your configured how-explainer model (default in [Models](#models))
- `readonly`: `true`

Build its prompt from `references/explainer-prompt.md` with every explorer's findings filled in.

## Step 4. Present

Present the explainer's output to the user. Light edits for clarity or context from the conversation are fine. Do not substantially rewrite it.

## Output Format

The explanation uses the sections defined in `references/explainer-prompt.md`, dropping any that do not apply: Overview, Key Concepts, How It Works, Where Things Live, Gotchas.

## Models

Role defaults originate from the upstream `plugins/pstack/models.json`. Refresh them through `scripts/vendor_jstack.py` after reviewing the upstream change. A matching role line in `~/.claude/jstack-models.md` overrides each at runtime; see `/setup-jstack`.

- how explorer: `claude-opus-5`
- how explainer: `claude-opus-5`

Attribution

jaydubya818jaydubya818
View sourceMore from jaydubya818 →
SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Related Skills

Caveman

Ultra-compressed communication mode that cuts output tokens while keeping technical accuracy. Levels: lite, full, ultra and the wenyan variants. Use for /caveman, "caveman mode", "talk like caveman", "be brief" or "less tokens".

1074701 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

693621 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3351 votes

catchup

Recovers the conversation and failed tool calls of a previous Codex, Claude Code, Antigravity, Cline, Copilot CLI, Cursor, DeepSeek Harness, Kimi, OpenCode, Pi Agent, or ZCode session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", asks to recover/summarize a previous session before continuing, or asks to diagnose or report a catchup failure. Do NOT use for the current conversation, git history, or any non-agent log.

691 votes

math-skill

A comprehensive mathematical reasoning skill for AI assistants — handles arithmetic to research-level problems with rigorous step-by-step reasoning, systematic verification, and transparent uncertainty handling

381 votes
View all in ai-agents →