Write well-structured notes that Basic Memory can parse into a searchable knowledge graph. Every note is a markdown file with three key sections: frontmatter, observations, and relations.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionmemory-notesExecute the skills CLI command in your project's root directory to begin installation:
Fetches memory-notes from basicmachines-co/basic-memory-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate memory-notes. Access via /memory-notes in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Write well-structured notes that Basic Memory can parse into a searchable knowledge graph. Every note is a markdown file with three key sections: frontmatter, observations, and relations.
---
title: API Design Decisions
tags: [api, architecture, decisions]
---
# API Design Decisions
The API team evaluated multiple approaches for the public API during Q1. After
prototyping both REST and GraphQL, the team chose REST due to broader ecosystem
support and simpler caching semantics. This note captures the key decisions and
their rationale, along with open questions still to resolve.
## Observations
- [decision] Use REST over GraphQL for simplicity #api
- [requirement] Must support versioning from day one
- [risk] Rate limiting needed for public endpoints
## Relations
- implements [[API Specification]]
- depends_on [[Authentication System]]
- relates_to [[Performance Requirements]]
Every note starts with YAML frontmatter:
---
title: Note Title # required — becomes the entity name in the knowledge graph
tags: [tag1, tag2] # optional — for organization and filtering
type: note # optional — defaults to "note", use custom types with schemas
permalink: custom-path # optional — auto-generated from title if omitted
---
title must match the # Heading in the bodytype values (Task, Meeting, Person, etc.) work with the schema system. See the memory-schema skill for defining schemas, validating notes against them, and detecting drift.permalink is auto-generated from the title and directory. For example, title "API Design Decisions" in directory "specs" produces permalink specs/api-design-decisions and memory URL memory://specs/api-design-decisions. If no directory is specified, the permalink is just the kebab-cased title. Permalinks stay stable across file moves. You rarely need to set one manually.Note: When using
write_note, you don't write frontmatter yourself. Thetitle,tags,note_type, andmetadataare separate parameters — Basic Memory generates the frontmatter automatically. Yourcontentparameter is just the markdown body starting with# Heading.
Free-form markdown between the heading and the Observations section. This is the heart of the note — write generously here:
Write complete, substantive prose. Basic Memory's search retrieves relevant chunks from note bodies, so longer, richer context makes notes more discoverable and more useful when found. Don't reduce everything to bullet points — tell the story.
Observations are categorized facts — the atomic units of knowledge. Each one becomes a searchable entity in the knowledge graph.
- [category] Content of the observation #optional-tag
The category in brackets is free-form — use whatever label makes sense for the observation. There is no fixed list. The only rule is the [category] content syntax. Consistency within a project helps searchability, but invent categories freely.
A few examples to illustrate the range:
- [decision] Use PostgreSQL for primary data store
- [risk] Third-party API has no SLA guarantee
- [technique] Exponential backoff for retry logic #resilience
- [question] Should we support multi-tenancy at the DB level?
- [preference] Use Bun over Node for new projects
- [lesson] Always validate webhook signatures server-side
- [status] active
- [flavor] Ethiopian beans work best with lighter roasts
[decision] Use JWT is less useful than [decision] Use JWT with 15-minute expiry for API auth.[risk] Rate limiting needed #api #security makes this findable under both topics.search_notes("[decision]") finds all decisions across your knowledge base.Relations create edges in the knowledge graph, linking notes to each other. They're how you build structure beyond individual notes.
- relation_type [[Target Note Title]]
[[...]] identify the target note by title or permalink| Type | Purpose | Example |
|---|---|---|
implements |
One thing implements another | - implements [[Auth Spec]] |
requires |
Dependencies | - requires [[Database Setup]] |
relates_to |
General connection | - relates_to [[Performance Notes]] |
part_of |
Hierarchy/composition | - part_of [[Backend Architecture]] |
extends |
Enhancement or elaboration | - extends [[Base Config]] |
pairs_with |
Things that work together | - pairs_with [[Frontend Client]] |
inspired_by |
Source material | - inspired_by [[CRDT Research Paper]] |
replaces |
Supersedes another note | - replaces [[Old Auth Design]] |
depends_on |
Runtime/build dependency | - depends_on [[MCP SDK]] |
contrasts_with |
Alternative approaches | - contrasts_with [[GraphQL Approach]] |
Wiki-links anywhere in the note body — not just the Relations section — also create graph edges:
We evaluated [[GraphQL Approach]] but decided against it because
the team has more experience with REST. See [[API Specification]]
for the full contract.
These create references relations automatically. Use the Relations section for explicit, typed relationships; use inline links for natural prose references.
[[Future Topic]] is valid — BM will resolve it when that note is created.build_context to traverse. build_context(url="memory://note-title") follows relations to gather connected knowledge.taught_by, blocks, tested_in — use whatever is descriptive.Every note is addressable via a memory:// URL, built from its permalink. These URLs are how you navigate the knowledge graph programmatically.
memory://api-design-decisions # by permalink (title → kebab-case)
memory://docs/authentication # by file path
memory://docs/authentication.md # with extension (also works)
memory://auth* # wildcard prefix
memory://docs/* # wildcard suffix
memory://project/*/requirements # path wildcards
In multi-project setups, prefix with the project name:
memory://main/specs/api-design # "main" project, "specs/api-design" path
memory://research/papers/crdt # "research" project
The first path segment is matched against known project names. If it matches, it's used as the project scope. Otherwise the URL resolves in the default project.
Memory URLs work with build_context to assemble related knowledge by traversing relations:
# Get a note and its connected context
build_context(url="memory://api-design-decisions")
# Wildcard — gather all docs
build_context(url="memory://docs/*")
# Direct read by permalink
read_note(identifier="memory://api-design-decisions")
Always search Basic Memory before creating a new note. Duplicates fragment your knowledge graph — updating an existing note is almost always better than creating a second one.
A single search often misses. Try the full name, abbreviations, acronyms, and keywords:
# Searching for an entity that might already exist
search_notes(query="Kubernetes Migration")
search_notes(query="k8s migration")
search_notes(query="container migration")
For people, try full name and last name. For organizations, try the full name and common abbreviations.
edit_note (append observations, add relations, find-and-replace outdated info)write_noteedit_noteWhen a note already exists, make targeted edits instead of rewriting the whole file:
# Append a new observation to an existing note
edit_note(
identifier="API Design Decisions",
operation="append",
section="Observations",
content="- [decision] Switched to OpenAPI 3.1 for spec generation #api"
)
# Fix outdated information
edit_note(
identifier="API Design Decisions",
operation="find_replace",
find_text="- [status] draft",
content="- [status] approved"
)
# Add a new relation
edit_note(
identifier="API Design Decisions",
operation="append",
section="Relations",
content="- depends_on [[Rate Limiter]]"
)
This preserves existing content and keeps the edit history clean.
write_note(
title="API Design Decisions",
directory="architecture",
tags=["api", "architecture"],
content="""# API Design Decisions
The API team evaluated REST and GraphQL during Q1 planning. After prototyping
both approaches, we chose REST for the public API — broader ecosystem support,
simpler caching with HTTP semantics, and a lower learning curve for external
consumers. GraphQL remains an option for internal services where query
flexibility matters more.
## Observations
- [decision] Use REST for public API #api
- [requirement] Support API versioning from v1
## Relations
- implements [[API Specification]]
- relates_to [[Backend Architecture]]"""
)
Basic Memory auto-generates frontmatter (including the permalink and memory URL) from the parameters. This note would get permalink architecture/api-design-decisions and be addressable at memory://architecture/api-design-decisions.
Use edit_note to append, prepend, or find-and-replace within a note:
# Append new observations
edit_note(
identifier="API Design Decisions",
operation="append",
section="Observations",
content="- [decision] Use OpenAPI 3.1 for spec generation #api"
)
# Add a new relation
edit_note(
identifier="API Design Decisions",
operation="append",
section=Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
Solid pick for teams standardizing on skills: memory-notes is focused, and the summary matches what you get after install.
memory-notes is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
memory-notes is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: memory-notes is focused, and the summary matches what you get after install.
Useful defaults in memory-notes — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
memory-notes has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend memory-notes for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: memory-notes is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend memory-notes for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
I recommend memory-notes for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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