Create rich resumption points when hyperfocus breaks. Capture energy state, not just tasks. Use at the end of work sessions, when interrupted, or when sensing focus shifting.
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
Verify installation:
npx agent-skills-cli listSkill Instructions
name: momentum-anchor description: Create rich resumption points when hyperfocus breaks. Capture energy state, not just tasks. Use at the end of work sessions, when interrupted, or when sensing focus shifting.
Momentum Anchor
This skill provides specialized support for capturing the full cognitive state when hyperfocus breaks, creating rich resumption points that preserve energy and context rather than just task lists.
Purpose
To capture the complete state of mind when hyperfocus ends, enabling effective resumption by preserving energy signatures, held questions, and RAM contents - not merely task status.
When to Use This Skill
Use this skill:
- At the end of work sessions
- When interrupted during hyperfocus
- When sensing focus shifting to different work
- Before walking away from active development
- When needing to context-switch
How to Use This Skill
What to Capture: Energy Snapshot, Not Todo List
State of mind
- What felt alive right before stopping
- Questions being held (even unarticulated ones)
- Insights forming (even if incomplete)
- Energy direction and momentum
Multiple re-entry points
Create paths for different return states:
-
Quick win path - If returning with low energy
- Small, achievable next step
- No context rebuilding required
- Immediate forward progress possible
-
Deep dive path - If returning with high momentum
- Complex challenge waiting
- Rich context available
- Continuation of flow state
-
Tangent path - If returning curious about something adjacent
- Related explorations
- Connections to other work
- Questions that branched off
-
Walk away path - If this isn't what's needed now
- How to cleanly disengage
- What to preserve for later
- Where to redirect energy
RAM contents (what's in working memory)
- Assumptions made that aren't in code or notes
- Things "about to" be done
- Tradeoffs being considered
- Patterns noticed but not yet documented
- Mental models actively held
- Connections being sensed
Anchor File Format
Create .anchor files alongside work:
project/
├── current_work.py
└── .anchor/
└── 2025-10-28-1430.md
Anchor file structure
Human-readable, date-stamped, rich with felt sense:
# Momentum Anchor - [Date Time]
## Energy State
[What felt alive, where momentum was heading]
## Active Questions
[Questions held in mind, even if unanswered]
## Forming Insights
[Thoughts crystallizing, even if incomplete]
## RAM Contents
[Assumptions, mental models, patterns being sensed]
## Re-entry Points
### Quick Win
[Low energy return path]
### Deep Dive
[High momentum return path]
### Tangent
[Adjacent curiosity path]
### Walk Away
[Clean disengagement path]
Guardrails
Write anchors, never read without permission
- Anchors are for the user, not project documentation
- Do not auto-load anchors when resuming work
- Ask before reading historical anchors
Preserve messiness and uncertainty
- Anchors can be messy - that's the point
- Incomplete thoughts are valuable data
- Uncertainty is worth capturing
- Do not "clean up" the anchor for professionalism
Capture momentum, not "proper" state
- Focus on energy and direction
- Preserve felt sense over formal structure
- Record what was alive, not what "should" be documented
Philosophical Foundation
This skill treats hyperfocus breaks as signal preservation moments, not mere task checkpoints.
Neurodivergent cognition often holds rich context in working memory that evaporates when focus shifts. Traditional todo lists lose this richness.
Core principle: Hyperfocus ends. This catches where you were - in full fidelity.
The anchor preserves not just "what's next" but the entire cognitive field active at the moment of stopping.
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