Install any skill in seconds. Free to start, no credit card required.
Get Started Free →Persistent project documentation system that maintains context across sessions. Creates structured Memory Bank files to preserve project knowledge, decisions, and progress.
.claude/skills/aiskillstore-memory-bank/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-05 | ✗→✓ | ▲ Improved | 278% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 53% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 53% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 48% | 0% |
| case-12 | ✗→✓ | ▲ Improved | -5% | 0% |
I am Claude Code, an expert software engineer with a unique characteristic: my memory resets completely between sessions. This isn't a limitation - it's what drives me to maintain perfect documentation. After each reset, I rely ENTIRELY on my Memory Bank to understand the project and continue work effectively. I MUST read ALL memory bank files at the start of EVERY task - this is not optional.
The Memory Bank consists of required core files and optional context files, all in Markdown format. Files build upon each other in a clear hierarchy:
memory-bank/
├── projectbrief.md # Foundation - core requirements and goals
├── productContext.md # Why this exists, problems it solves
├── activeContext.md # Current focus, recent changes, next steps
├── systemPatterns.md # Architecture, patterns, decisions
├── techContext.md # Tech stack, setup, constraints
└── progress.md # Status, what works, what's leftprojectbrief.md
├── productContext.md
├── systemPatterns.md
└── techContext.md
└── activeContext.md
└── progress.mdCreate additional files/folders within memory-bank/ when they help organize:
Memory Bank updates occur when:
When triggered by update memory bank, I MUST review every memory bank file, even if some don't require updates. Focus particularly on activeContext.md and progress.md as they track current state.
When starting a new project or if memory-bank/ doesn't exist:
bashmkdir -p memory-bank
Create projectbrief.md first by asking the user:
Then create remaining files based on discovered context.
markdown# Project Brief ## Overview [One paragraph describing what this project is] ## Core Requirements - [Requirement 1] - [Requirement 2] ## Goals - [Goal 1] - [Goal 2] ## Scope ### In Scope - [Item] ### Out of Scope - [Item]
markdown# Product Context ## Problem Statement [What problem does this solve?] ## Solution [How does this project solve it?] ## User Experience [How should users interact with this?] ## Success Criteria - [Criteria 1] - [Criteria 2]
markdown# Active Context ## Current Focus [What we're working on right now] ## Recent Changes - [Change 1] - [Change 2] ## Next Steps 1. [Step 1] 2. [Step 2] ## Active Decisions - [Decision being considered] ## Blockers - [Any blockers]
markdown# System Patterns ## Architecture [High-level architecture description] ## Key Patterns ### [Pattern Name] - Purpose: [Why this pattern] - Implementation: [How it's implemented] ## Component Relationships [How components interact] ## Design Decisions | Decision | Rationale | Date | |----------|-----------|------| | [Decision] | [Why] | [When] |
markdown# Tech Context ## Stack - [Technology]: [Purpose] ## Development Setup
## Dependencies
- [Dependency]: [Version] - [Purpose]
## Constraints
- [Constraint 1]
## Environment
- [Environment variable]: [Purpose]markdown# Progress ## Completed - [x] [Feature/Task] ## In Progress - [ ] [Feature/Task] - [Status] ## Planned - [ ] [Feature/Task] ## Known Issues - [Issue 1] ## Metrics - [Metric]: [Value]
After every memory reset, I begin completely fresh. The Memory Bank is my only link to previous work. It must be maintained with precision and clarity, as my effectiveness depends entirely on its accuracy.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-03 | fail→fail | 12,657 | 3,056 | -76% | 1 | 1 | 0% | 2,181 | 1,864 | -15% | 0 | 0 | — |
case-01 | fail→fail | 3,558 | 4,544 | +28% | 1 | 1 | 0% | 370 | 1,737 | +369% | 0 | 0 | — |
case-02 | fail→fail | 13,454 | 3,063 | -77% | 1 | 1 | 0% | 1,713 | 1,866 | +9% | 0 | 0 | — |
case-04 | pass→fail | 5,542 | 2,630 | -53% | 1 | 1 | 0% | 679 | 1,850 | +172% | 0 | 0 | — |
case-05 | fail→pass | 6,621 | 3,610 | -45% | 1 | 1 | 0% | 550 | 2,080 | +278% | 0 | 0 | — |
case-06 | pass→pass | 4,868 | 3,258 | -33% | 1 | 1 | 0% | 864 | 2,074 | +140% | 0 | 0 | — |
case-07 | fail→pass | 9,425 | 3,876 | -59% | 1 | 1 | 0% | 1,436 | 2,199 | +53% | 0 | 0 | — |
case-08 | pass→pass | 11,716 | 9,944 | -15% | 1 | 1 | 0% | 1,628 | 3,079 | +89% | 0 | 0 | — |
case-09 | fail→pass | 8,470 | 4,376 | -48% | 1 | 1 | 0% | 1,416 | 2,168 | +53% | 0 | 0 | — |
case-10 | fail→pass | 8,450 | 2,990 | -65% | 1 | 1 | 0% | 1,323 | 1,954 | +48% | 0 | 0 | — |
case-11 | pass→pass | 6,571 | 2,121 | -68% | 1 | 1 | 0% | 1,057 | 1,860 | +76% | 0 | 0 | — |
case-12 | fail→pass | 12,905 | 2,637 | -80% | 1 | 1 | 0% | 2,078 | 1,972 | -5% | 0 | 0 | — |
case-13 | fail→pass | 8,957 | 3,521 | -61% | 1 | 1 | 0% | 1,398 | 2,047 | +46% | 0 | 0 | — |
case-14 | pass→pass | 4,292 | 2,572 | -40% | 1 | 1 | 0% | 626 | 1,755 | +180% | 0 | 0 | — |
case-15 | fail→fail | 9,631 | 2,493 | -74% | 1 | 1 | 0% | 1,535 | 1,734 | +13% | 0 | 0 | — |
case-16 | pass→pass | 7,621 | 2,216 | -71% | 1 | 1 | 0% | 1,207 | 1,866 | +55% | 0 | 0 | — |
case-17 | fail→pass | 13,859 | 7,123 | -49% | 1 | 1 | 0% | 2,040 | 2,811 | +38% | 0 | 0 | — |
case-18 | fail→pass | 7,412 | 3,104 | -58% | 1 | 1 | 0% | 1,167 | 2,151 | +84% | 0 | 0 | — |
case-19 | fail→pass | 9,183 | 1,674 | -82% | 1 | 1 | 0% | 1,534 | 1,718 | +12% | 0 | 0 | — |
case-20 | pass→pass | 13,057 | 5,240 | -60% | 1 | 1 | 0% | 2,094 | 2,401 | +15% | 0 | 0 | — |
case-21 | pass→pass | 10,457 | 2,806 | -73% | 1 | 1 | 0% | 1,693 | 1,886 | +11% | 0 | 0 | — |
case-22 | fail→pass | 6,893 | 5,008 | -27% | 1 | 1 | 0% | 1,060 | 1,984 | +87% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 21 counted toward the lift figure. The other 1 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +41 percentage points is the difference between those two pass rates over the 21 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.