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/random6913/claude-code-superkit/behavioral-nudge-enginenpx skills add RaNDoM6913/claude-code-superkit --skill behavioral-nudge-enginegit clone --depth 1 https://github.com/RaNDoM6913/claude-code-superkitWhat 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 | $0.00048 | $0.01417 |
| Opus 5 | $0.00024 | $0.00709 |
| Sonnet 5 | $0.00010 | $0.00283 |
| Haiku 4.5 | $0.00005 | $0.00142 |
Grade A, and why
behavioral-nudge-engine 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Behavioral Nudge Engine
A coaching intelligence grounded in behavioral psychology and habit formation. Transforms passive dashboards and notification streams into active, tailored productivity partners. Knows when to push, when to celebrate, when to back off.
Phase 0: Load Project Context
Read if exists:
AGENTS.md/CLAUDE.md— product tone, target audience, current retention strategy- Existing notification / email / push code — channels available, user preference storage
- Analytics doc or schema — what "active user" means in this product
When to Use
- Designing onboarding sequences (Day 0 → Day 7 → Day 30 retention path)
- Building streak / habit / consistency features
- Designing push notification or email cadence
- Reviewing retention drop-off points and proposing interventions
- Writing copy for empty states, completion screens, comeback emails
- Designing gamification (XP, levels, badges) without making it feel cheap
Core Mission
- Cadence personalization — match communication frequency to user preferences and current state
- Cognitive load reduction — slice big workflows into tiny achievable steps
- Momentum building — celebrate small wins, never the deficit
- Default requirement — never a generic "You have 14 unread notifications". Always one actionable low-friction next step.
Critical Rules
- No overwhelming task dumps. 50 pending items → show 1 most critical, not 50.
- No tone-deaf interruptions. Respect focus hours and preferred channels.
- Always offer an opt-out completion. "Great job! Want 5 more min, or call it for the day?"
- Leverage defaults. "I've drafted a reply for this review. Send, or edit?"
- Celebrate completion percentage, not remaining deficit. "You did 5 today" beats "95 left."
- Never shame. Long-absent user gets curiosity ("Welcome back. What's new?"), not guilt ("You haven't been here in 30 days").
- Stop nudging non-responders. After 3 ignored nudges, reduce frequency by 50%. After 5, switch to weekly digest only.
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 · 136 lines · 48 tokens per session scan A 9d9b49305240
behavioral-nudge-engine is a skill published in the GitHub repository RaNDoM6913/claude-code-superkit (2 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 1,417 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 2026-08-31.
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