Engram is a local or cloud-backed memory system for AI coding agents, provided as a single Go binary with SQLite full-text search and interfaces including a command line, HTTP API, MCP server, and terminal UI. It helps compatible coding agents retain project decisions, bugs, conventions, and other useful context across sessions. The catalogue add-ons configure and operate Engram’s memory workflows.
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 skills/gentleman-programming/engram/gentleman-bubbleteanpx skills add Gentleman-Programming/engram --skill gentleman-bubbleteagit clone --depth 1 https://github.com/Gentleman-Programming/engramWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gentleman-programming/engram/gentleman-bubbletea)<a href="https://agentmods.dev/skills/gentleman-programming/engram/gentleman-bubbletea"><img src="https://agentmods.dev/badge/skills/gentleman-programming/engram/gentleman-bubbletea.svg" alt="Measured on agentmods" height="20"></a>What 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 5.1 | $0.00042 | $0.01448 |
| Opus 5 | $0.00021 | $0.00724 |
| Sonnet 5 | $0.00008 | $0.00290 |
| Haiku 4.5 | $0.00004 | $0.00145 |
Grade A, and why
gentleman-bubbletea 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 6d ago.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- gentleman-bubbletea — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 250 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to Use
Use this skill when:
- Adding new screens to the TUI installer
- Handling keyboard input or navigation
- Creating new UI components with Lipgloss
- Working on screen transitions or state management
Critical Patterns
Pattern 1: Screen Constants in model.go
All screens MUST be defined as Screen constants in model.go:
type Screen int
const (
ScreenWelcome Screen = iota
ScreenMainMenu
ScreenOSSelect
// ... new screens go here
ScreenNewFeature // Add new screen
ScreenNewFeatureCat // Add category screen if needed
)
Pattern 2: Model Struct Holds All State
The Model struct in model.go holds ALL application state:
type Model struct {
Screen Screen
PrevScreen Screen // For back navigation
Width int
Height int
Cursor int
// Add new state here
NewFeatureData []SomeType
NewFeatureScroll int
}
Pattern 3: Update Pattern with Type Switch
All input handling goes through Update() with a type switch:
func (m Model) Update(msg tea.Msg) (tea.Model, tea.Cmd) {
switch msg := msg.(type) {
case tea.KeyMsg:
return m.handleKeyPress(msg)
case tea.WindowSizeMsg:
m.Width = msg.Width
m.Height = msg.Height
return m, nil
case customMsg:
// Handle custom messages
return m, nil
}
return m, nil
}
Pattern 4: Key Handlers Return (Model, Cmd)
Separate handler per screen, always return (tea.Model, tea.Cmd):
func (m Model) handleNewFeatureKeys(key string) (tea.Model, tea.Cmd) {
options := m.GetCurrentOptions()
switch key {
case "up", "k":
if m.Cursor > 0 {
m.Cursor--
// Skip separator
if strings.HasPrefix(options[m.Cursor], "───") && m.Cursor > 0 {
m.Cursor--
}
}
case "down", "j":
if m.Cursor < len(options)-1 {
m.Cursor++
if strings.HasPrefix(options[m.Cursor], "───") && m.Cursor < len(options)-1 {
m.Cursor++
}
}
case "enter", " ":
// Handle selection
return m.handleNewFeatureSelection()
case "esc":
m.Screen = m.PrevScreen
m.Cursor = 0
}
return m, nil
}
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.
- 6d ago First seen · 250 lines · 42 tokens per session scan A 93c836b6a941
gentleman-bubbletea is a skill published in the GitHub repository Gentleman-Programming/engram (6,326 stars, last pushed today), licensed MIT. It adds 42 tokens to every session and 1,448 once invoked, about $0.0002 per session on Opus 5. 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 2026-08-30.
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