AI DevKit Memory CLI
SkillSearchAI DevKit · Use the memory CLI as a durable knowledge layer. Search before non-trivial work, store verified reusable knowledge, update stale entries, and avoid saving transcripts, secrets, or one-off task progress.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the AI DevKit Memory CLI skill
What this skill tells your AI
The instructions your AI receives, as published by codeaholicguy/ai-devkit in skills/memory/SKILL.md and read by ahel’s review.
Use npx ai-devkit@latest memory ... as the durable knowledge layer.
Workflow
-
For implementation, debugging, review, planning, or documentation tasks, search before deep work unless the task is trivial:
npx ai-devkit@latest memory search --query "<task, subsystem, error, or convention>" --limit 5For broad or risky tasks, search multiple angles: subsystem, error text, framework, command, and task intent.
-
Use results as context:
- Trust repo files, tests, fresh command output, and explicit user instructions over memory.
- If memory conflicts with verified evidence, use the evidence and update the stale memory.
- Mention memory only when it changes the plan or avoids asking the user again.
-
Search before storing:
npx ai-devkit@latest memory search --query "<knowledge to store>" --table -
Store or update only after the quality gate passes.
Quality Gate
Before storing, all must be true:
- Future sessions are likely to reuse it.
- It is verified by code, docs, tests, command output, or explicit user instruction.
- It is not merely a restatement of obvious nearby files unless it prevents repeated agent mistakes.
- It is scoped narrowly enough.
- Existing memory does not already cover it.
- It contains no secrets, credentials, private customer data, personal data, raw logs, or temporary paths.
Store:
- Project conventions, user preferences, durable decisions.
- Reusable fixes, testing patterns, commands, setup gotchas.
- Non-obvious constraints, architecture rules, failure patterns.
Do not store:
- Task progress, transcripts, speculation, generic programming facts.
- Raw errors without diagnosis.
- Anything the user did not intend to persist.
Commands
Search
npx ai-devkit@latest memory search \
--query "<query>" \
--tags "<tags>" \
--scope "<scope>" \
--limit 5
Use --table to get IDs for updates:
npx ai-devkit@latest memory search --query "<query>" --table
Options: --query/-q required; --tags; --scope/-s; --limit/-l from 1-20; --table.
Store
npx ai-devkit@latest memory store \
--title "<actionable title, 10-100 chars>" \
--content "<context, guidance, evidence, exceptions>" \
--tags "<lowercase,tags>" \
--scope "<global|project:name|repo:org/repo>"
Use this content shape when helpful:
Context: Where this applies.
Guidance: What to do.
Evidence: File, command, test, or user instruction.
Exceptions: When not to apply it.
Update
Find the ID with search --table, then update only changed fields:
npx ai-devkit@latest memory update \
--id "<memory-id>" \
--title "<updated title>" \
--content "<updated content>" \
--tags "<replacement,tags>" \
--scope "<updated scope>"
--tags replaces all existing tags.
Scoping
Use the narrowest useful scope:
repo:<org/repo>for one repository.project:<name>for one app, product, or workspace.globalonly for knowledge that applies across unrelated projects.
If unsure, use a narrower scope.
Troubleshooting
- CLI missing: run
npx ai-devkit@latest --version. - Duplicate title: search, then update the existing item if it is the same knowledge.
- Empty results: broaden terms, remove filters, or search symptoms and subsystem names separately.
- Validation error: check title/content lengths, query length, and
--limitrange. - DB path: default is
~/.ai-devkit/memory.db; project config can override it automatically.
Signals
- GitHub stars
- 2k
- Forks
- 250
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
memory-codeaholicguy- Source
- github.com/codeaholicguy/ai-devkit