Auto-Company is a software system that runs a recurring team of AI agents on a personal computer, where the agents plan work, make decisions, write code, deploy applications, and handle marketing. It is intended for autonomous product development on Windows, Linux, or macOS, using command-line agent tools and a local dashboard to track cycles and results. The catalogue entries are skills, agents, settings, and instructions that support this automated workflow.
Borrowing it
Nothing to install: this file belongs to MaxMiksa/Auto-Company. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/MaxMiksa/Auto-Company/main/.claude/skills/deep-reading-analyst/SKILL.mdgit clone --depth 1 https://github.com/MaxMiksa/Auto-CompanyWrote 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/skills/maxmiksa/auto-company/deep-reading-analyst)<a href="https://agentmods.dev/skills/maxmiksa/auto-company/deep-reading-analyst"><img src="https://agentmods.dev/badge/skills/maxmiksa/auto-company/deep-reading-analyst/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/maxmiksa/auto-company/deep-reading-analyst"><img src="https://agentmods.dev/badge/skills/maxmiksa/auto-company/deep-reading-analyst.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00169 | $0.03598 |
| Opus 5.5 | $0.00068 | $0.01439 |
| Sonnet 5.5 | $0.00034 | $0.00720 |
| Haiku 4.5 | $0.00017 | $0.00360 |
Grade A, and why
deep-reading-analyst 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 1mo 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.
Copies of this mod
4 near-identical copies found in the catalogue:
- deep-reading-analyst — 100% identical, 0 lines differ
- deep-reading-analyst — 100% identical, 0 lines differ
- deep-reading-analyst — 100% identical, 0 lines differ
- deep-reading-analyst — 91% identical, 5 lines differ
How it starts
The opening of the file, as written. The whole thing — 502 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Reading Analyst
Transforms surface-level reading into deep learning through systematic analysis using 10+ proven thinking frameworks. Guides users from understanding to application through structured workflows.
Framework Arsenal
Quick Analysis (15min)
- 📋 SCQA - Structure thinking (Situation-Complication-Question-Answer)
- 🔍 5W2H - Completeness check (What, Why, Who, When, Where, How, How much)
Standard Analysis (30min)
- 🎯 Critical Thinking - Argument evaluation
- 🔄 Inversion Thinking - Risk identification
Deep Analysis (60min)
- 🧠 Mental Models - Multi-perspective analysis (physics, biology, psychology, economics)
- ⚡ First Principles - Essence extraction
- 🔗 Systems Thinking - Relationship mapping
- 🎨 Six Thinking Hats - Structured creativity
Research Analysis (120min+)
- 📊 Cross-Source Comparison - Multi-article synthesis
Workflow Decision Tree
User provides content
↓
Ask: Purpose + Depth Level + Preferred Frameworks
↓
┌─────────────────┬─────────────────┬─────────────────┬─────────────────┐
│ Level 1 │ Level 2 │ Level 3 │ Level 4 │
│ Quick │ Standard │ Deep │ Research │
│ 15min │ 30min │ 60min │ 120min+ │
├─────────────────┼─────────────────┼─────────────────┼─────────────────┤
│ • SCQA │ Level 1 + │ Level 2 + │ Level 3 + │
│ • 5W2H │ • Critical │ • Mental Models │ • Cross-source │
│ • Structure │ • Inversion │ • First Princ. │ • Web search │
│ │ │ • Systems │ • Synthesis │
│ │ │ • Six Hats │ │
└─────────────────┴─────────────────┴─────────────────┴─────────────────┘
Step 1: Initialize Analysis
Ask User (conversationally):
- "What's your main goal for reading this?"
- Problem-solving / Learning / Writing / Decision-making / Curiosity
- "How deep do you want to go?"
- Quick (15min) / Standard (30min) / Deep (60min) / Research (120min+)
- "Any specific frameworks you'd like to use?"
- Suggest based on content type (see Framework Selection Guide below)
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/5w2h_analysis.md 8.8 KB
- references/comparison_matrix.md 8.7 KB
- references/critical_thinking.md 3.2 KB
- references/first_principles.md 4.4 KB
- references/inversion_thinking.md 8.5 KB
- references/mental_models.md 8.5 KB
- references/output_templates.md 7.5 KB
- references/scqa_framework.md 11 KB
- references/six_hats.md 7.7 KB
- references/systems_thinking.md 5.6 KB
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.
- 1mo ago First seen · 502 lines · 169 tokens per session scan A afebad75f8a7
deep-reading-analyst is a skill published in the GitHub repository MaxMiksa/Auto-Company (3,156 stars, last pushed 2d ago), licensed MIT. It adds 169 tokens to every session and 3,598 once invoked, about $0.0007 per session on Opus 5.5. 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 2026-08-30.
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