Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/rustkit-ai/aimemo/copilotgit clone --depth 1 https://github.com/rustkit-ai/aimemoWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00850 |
| Opus 5 | $0.00000 | $0.00425 |
| Sonnet 5 | $0.00000 | $0.00170 |
| Haiku 4.5 | $0.00000 | $0.00085 |
Grade A, and why
copilot scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
aimemo × GitHub Copilot / VS Code
GitHub Copilot reads .github/copilot-instructions.md automatically in VS Code and JetBrains IDEs. aimemo setup writes instructions into that file telling Copilot to maintain the memory loop: inject context at session start, log after file edits, recap at session end.
VS Code users: use
aimemo inject --vscode— it writes to the same file.
Setup
Run once in your project root:
aimemo setup --copilot
Then bootstrap from your git history so the agent has context from day one:
aimemo bootstrap
What gets written
.github/copilot-instructions.md (appended section):
## aimemo — persistent memory
- At session start: run `aimemo inject --copilot` to load context from previous sessions
- After modifying any file: run `aimemo log "modified {filename}: {one-line reason}"`
- When you identify something to fix later: run `aimemo log "todo: {description}"`
- At session end: run `aimemo recap "{what was done} — next: {what comes next}"` then `aimemo inject --copilot`
<!-- aimemo:start -->
## aimemo context
last: (no entries yet)
<!-- aimemo:end -->
If a
copilot-instructions.mdalready exists,aimemo setupappends the block instead of overwriting the file.
The session loop
Open VS Code / JetBrains with Copilot
│
▼
Copilot reads .github/copilot-instructions.md
│
▼
Agent runs: aimemo inject --copilot
│ (updates the context block in copilot-instructions.md)
▼
Agent reads the context — knows where it left off
│
▼
You work — agent logs after each file edit:
aimemo log "modified src/components/Button.tsx: extracted shared component"
aimemo log "todo: update Storybook stories for Button"
│
▼
At session end:
aimemo recap "extracted Button component, replaced 12 usages — next: Storybook"
aimemo inject --copilot
│
▼
Next session starts with full context
What the context block looks like
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 135 lines · 0 tokens per session scan A 88c9d4617696
copilot is an agent published in the GitHub repository rustkit-ai/aimemo (4 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 850 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
builder
Turn shot-plan.json into one renderable HyperFrames composition (compositions/index.html). Everything stays in the HF ecosystem — HTML is the source of truth; a single paused GSAP timeline carries all motion; the engine seeks it. Category-specific build rules live in categories/ /module.md; this file is the shared…
MEMORY
Generalized reusable lessons from agent sessions. Root causes converted into preventive rules, not incident-specific notes. Entries are h3 headers with [ACTIVE|RETIRED] status. Content: brief, grep-friendly, MECE across sections. Style: one-liner per entry, optional sub-bullets for context.
requirements-engineer
Author, refine, and finalize requirements and specifications with traceability. Full subagent.
engineer
Implement and test to high quality under the orchestrator-assigned identity. Full subagent.
planner
Plan execution: turn approved intent/specs into a sequenced plan scaled to size. Full subagent.
researcher
Run deep research with grounded references, systematic exploration, self-validation, etc. Full subagent.