What makes Deep Work notable?

1.1K downloads. Trust evidence available

How should Deep Work be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Deep Work

Activate when: user says 'I can never find time for focused work', 'I feel busy but produce nothing', 'I keep getting interrupted', 'I want to protect my foc... Skill: Deep Work Owner: deciqai Summary: Activate when: user says 'I can never find time for focused work', 'I feel busy but produce nothing', 'I keep getting interrupted', 'I want to protect my foc... Tags: latest:1.0.5 Version history: v1.0.5 | 2026-07-16T17:57:05.645Z | user Description tail link + agents machine-readable metadata line (deciqai.com/s/deep-work.json) v1.0.4 | 2026-07-10T10:24:46.922Z | user Add 202

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.1k

Updated

Oct 11, 2026

Version

1.0.5

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.1K downloads reported by the source. Last updated 10/11/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1.1K downloadsadoption · observed Oct 11, 2026
Latest release: 1.0.5release · observed Jul 16, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17a4mqcnk515kvaca5ze55d0x88pfpx:deep-work

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-deciqai-deep-work/snapshot"

Documentation

CLAWHUB

143,687 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: deep-work
description: "Activate when: user says 'I can never find time for focused work', 'I feel busy but produce nothing', 'I keep getting interrupted', 'I want to protect my focus time', 'flow state', 'deliberate practice', 'Cal Newport', or asks how to make progress on hard cognitive work (research, writing, engineering, strategy). Do NOT activate when: the role is genuinely high-coordination with no discrete focus windows (ER medicine, real-time trading desk), or user is in a short-term emergency where availability must dominate. More: deciqai.com/c/deep-work"
---

# Deep Work

## Overview

Cal Newport's framework (2016): **deep work** = undistracted, cognitively demanding activity that creates hard-to-replicate value; **shallow work** = logistical, responsive, easy-to-replicate work that fills modern calendars. The most valuable knowledge work is disproportionately the product of deep work; shallow work is increasingly automatable. Three foundations: attention research shows 15-25 min recovery cost per interruption; expert performance requires deliberate practice (structurally a form of deep work); the opportunity cost of shallow work is invisible — no one tracks which deep work didn't happen this week.

Composes with `wu-wei` (flow as the felt experience), `metacognition` (monitoring drift out of deep mode), `okr-goal-setting` (OKRs give deep work direction), `pareto-principle` (the 20% producing 80% of value is almost always deep work).

## When to Use

- Output depends on hard-to-replicate cognitive work (research, engineering, writing, design, strategy)
- Calendar fragmentation prevents the work that actually matters; weeks feel busy but produce nothing
- High-stakes project requires extended concentration; career advancement depends on skill development
- AI copilots / assistants have become another interruption stream ("is AI helping my focus or fragmenting it?", "AI adoption vs deep work", "AI hype and staying focused")

**Not when:** genuinely high-coordination roles where deep work is structurally impossible; already done with deep work and shallow follow-through is now required; short-term emergency where availability dominates.

## Coaching Novices (Adaptive Front Door)

- **Engine mode:** user has a concrete case → run The Process directly.
- **Coach mode:** user unfamiliar or has no concrete case → guide step by step.

In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.

1. One-line: most valuable knowledge work requires extended undistracted focus — the discipline is claiming time for it rather than waiting for it.
2. Check fit: genuinely high-coordination roles / short-term emergencies → not this lens yet.
3. Elicit the specific work that requires depth — what's not getting done?
> **[WAIT — do not advance until user responds]**
4. One question at a time: what's your deep-vs-shallow ratio? What's the highest-leverage deep work? What's the cost of not

_meta.json

{
  "ownerId": "kn754b8sk22s8c6gjxt02bftbn88q7ye",
  "slug": "deep-work",
  "version": "1.0.5",
  "publishedAt": 1784224625645
}

references/sources.md

# Sources — deep-work

> *Primary sources for the [deep-work](../SKILL.md) skill.*

- Newport, C. (2016). *Deep Work: Rules for Focused Success in a Distracted World.* Grand Central. ISBN 978-1455586691. The canonical articulation.
- Knuth, D. E. (1990 / ongoing). "Knuth versus Email." Stanford homepage. https://www-cs-faculty.stanford.edu/~knuth/email.html. The earliest extreme-deep-work case study with the practitioner's own documentation.
- Jung, C. G. (1962). *Memories, Dreams, Reflections.* Recorded and edited by Aniela Jaffé; trans. Richard and Clara Winston (1963). Pantheon. The chapter "The Tower" is Jung's own account of the Bollingen retreat practice — the canonical bimodal case.
- Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). "The Role of Deliberate Practice in the Acquisition of Expert Performance." *Psychological Review*, 100(3), 363-406. The foundational empirical paper on expert performance and deliberate practice.
- Mark, G., Gudith, D., & Klocke, U. (2008). "The Cost of Interrupted Work: More Speed and Stress." *CHI 2008 Proceedings*. The empirical psychology of attention-switching.
- Leroy, S. (2009). "Why is it so hard to do my work? The challenge of attention residue when switching between work tasks." *Organizational Behavior and Human Decision Processes*, 109(2), 168-181. The "attention residue" concept.
- Csikszentmihalyi, M. (1990). *Flow: The Psychology of Optimal Experience.* Harper & Row. ISBN 978-0061339202. The experiential side of deep work.
- Newport, C. (2019). *Digital Minimalism: Choosing a Focused Life in a Noisy World.* Portfolio. ISBN 978-0525536512. The companion volume on personal-life dimensions.
- Carr, N. (2010). *The Shallows: What the Internet Is Doing to Our Brains.* Norton. ISBN 978-0393339758. The cultural diagnosis of why deep work has become rare.
- GitHub (2022, June 21). "GitHub Copilot is generally available to all developers." https://github.blog/2022-06-21-github-copilot-is-generally-available-to-all-developers/. Marks the mainstreaming of AI copilots in daily knowledge work — the 2024–2026 context for the deep/shallow distinction.
- Newport, C. (2024–2025). *Deep Questions* podcast and essays on AI and knowledge work. https://calnewport.com. Newport's contemporary argument that undistracted human cognition rises in value as routine output is automated.

examples/carl-jung-bollingen-tower-retreats.md

# Method in Action: Carl Jung's Bollingen Tower Retreats (1923–1961)

> *Example for the [deep-work](../SKILL.md) skill.*

Carl Jung's Bollingen tower is the case Cal Newport chose to open *Deep Work* (2016), and it remains the cleanest historical demonstration of the **Bimodal philosophy**: a working psychiatrist who could not abandon his shallow obligations, and instead built a physical architecture for alternating between them and depth.

**The diagnosis (Steps 1-2):** In the 1920s Jung's professional life in Zurich and Küsnacht was structurally shallow-saturated: a busy clinical practice with a full patient load, lectures, seminars, and heavy correspondence. This was also the period in which Jung was establishing analytical psychology as an independent school after his break with Freud — an intellectual project competing against the most formidable rival imaginable. The highest-leverage deep work was unambiguous: the sustained theoretical writing that would define archetypes, the collective unconscious, and individuation. That writing could not happen between patient sessions. Jung did not need a tracking week to see the ratio; the clinical calendar made it visible.

**The philosophy choice (Step 3):** Jung could not go monastic — his clinical practice was both his income and his empirical material. He chose the bimodal split: full engagement with practice and public life in Zurich, then regular retreats to a private refuge for concentrated writing.

**The practice (Step 4):** In 1922 Jung bought land at Bollingen on the upper lake of Zurich, and beginning in 1923 built a stone tower there by stages, expanding it over the following decades. The tower was deliberately spartan — no electricity; Jung chopped his own wood, drew his own water, and lit oil lamps. In *Memories, Dreams, Reflections* (1962), the chapter "The Tower" describes the place in Jung's own account as a site of repose and renewal where he felt most deeply himself — a purpose-built container for concentration. Newport reconstructs the working rhythm: mornings locked in a private study for undisturbed writing, afternoons given to meditation and walks, early nights. Same location, same setup, hard boundary — the full ritual structure of Step 4, implemented in stone.

**Shallow reduction and defense (Steps 5-6):** Every Bollingen period was clinical income refused and patients turned away — the shallow-work budget enforced at direct financial cost. The retreats could look like withdrawal from a career; they were its engine. The output produced across four decades of this regime — the essays and books that became the *Collected Works* and established analytical psychology as a lasting school — is the long-term evidence Step 6 says to accumulate: output value as the defense of the practice.

The structural lesson mirrors Knuth's but from the opposite pole: Knuth shows the monastic extreme (eliminate the shallow channel permanently); Jung shows that a practitioner who *cannot* elimin

examples/deep-work-amid-ai-copilots-2024-2026.md

# Method in Action: Protecting Deep Work Amid AI Copilots (2024–2026)

> *Example for the [deep-work](../SKILL.md) skill.*

Between 2022 and 2026, generative-AI copilots moved from novelty to default fixture of knowledge work. GitHub Copilot became generally available in June 2022; ChatGPT launched in November 2022; and by 2024–2025 assistants were embedded directly into the tools where work happens — IDEs (Copilot, Cursor), office suites (Microsoft 365 Copilot, Google's Gemini in Workspace), and communication tools. The promise was more focus. The lived experience for many knowledge workers was the opposite: **another always-on stream demanding attention** — suggestions to accept or reject, chat panels to consult, notifications, and a new social pressure to "use the AI." This example runs a composite knowledge worker — a senior software engineer, call her Maya — through the deep-work Process to decide how AI should relate to her focus rather than fragment it.

The core tension is exactly the deep/shallow distinction Newport drew in 2016, now with a new actor. An AI copilot can serve deep work (as a tool inside a protected block) or become shallow work (another interruption stream, another inbox). The framework's job is to keep it the former.

**Step 1 — Instrument.** Maya tracks one week. Her estimate before tracking: "maybe 4 hours a day of real focused coding." The tracked reality: roughly 1–1.5 hours of genuinely uninterrupted deep work per day, scattered in fragments. The new finding specific to 2024–2026: a meaningful share of her fragmentation now comes from *AI-adjacent* micro-switches — pausing mid-thought to prompt a chatbot, context-switching to read and evaluate a generated suggestion, and tab-hopping between editor and assistant. The copilot did not remove interruptions; it added a self-inflicted one that feels productive. This matches the widely-reported pattern in industry research on developer experience: perceived productivity gains from AI tools coexist with fragmented attention, and the recovery cost of task-switching (the 2008 Mark et al. and 2009 Leroy attention-residue findings) does not disappear just because the interruption is a helpful one.

```
- Deep work hours/day (tracked): ~1.25 | Shallow hours/day: ~5 | Ratio: poor
- Surprise factor: high — AI prompting felt like focus but registered as switching
```

**Step 2 — Identify.** The highest-leverage deep work is the hard, hard-to-replicate cognitive work: system design, reasoning about a subtle concurrency bug, and the architectural decisions that shape months of downstream code. This is precisely the class of work that current AI models assist *least* well — they accelerate boilerplate, recall, and first-draft scaffolding, but the load-bearing judgment (what to build, why, and what breaks at scale) still resists being outsourced. Why isn't the deep work happening? Because the day is saturated with shallow work — and now the copilot, if used reflexively, invites her to

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