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 commands/javanc/homunculus/hm-nightgit clone --depth 1 https://github.com/JavanC/HomunculusWrote 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/commands/javanc/homunculus/hm-night)<a href="https://agentmods.dev/commands/javanc/homunculus/hm-night"><img src="https://agentmods.dev/badge/commands/javanc/homunculus/hm-night.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 | $0.00000 | $0.02789 |
| Opus 5 | $0.00000 | $0.01394 |
| Sonnet 5 | $0.00000 | $0.00558 |
| Haiku 4.5 | $0.00000 | $0.00279 |
Grade A, and why
hm-night 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.
How it starts
The opening of the file, as written. The whole thing — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/hm-night — Run One Evolution Cycle
Run the evolution pipeline. Depth depends on evolution-config.yaml (tier + schedule).
Always communicate in English regardless of user's global Claude settings.
Evolution Config
Read evolution-config.yaml from the project root at the start. If missing, default to tier: standard.
Tier controls what runs:
minimal— Phase 1 (health) + Phase 2 (instinct routing only) + Phase 5 (report). Skip research & experiments.standard— All phases. Research:research.topics_min-research.topics_maxtopics. Experiments:experiments.max_per_night.full— All phases + deeper research + more experiments + bonus loop.
Weekly schedule:
- Check
schedule.weekly.day(0=Sun..6=Sat, -1=every day). - If today matches → run weekly deep mode: full skill re-eval, goal tree mechanism review, deep health check.
- Otherwise → run daily light mode: instinct routing + changed skill eval only.
Core Principle
Goals are stable. Implementations are diverse. When suggesting improvements, consider ALL implementation types — not just skills:
| Type | When to suggest |
|---|---|
| Skill | Behavioral knowledge Claude should follow |
| Agent | Task needs specialized model/tools/prompt |
| Hook | Should trigger automatically on events |
| Script | Automation that runs independently |
| Rule | Claude Code behavioral constraint |
| Command | Workflow the user triggers manually |
| Cron/LaunchAgent | Needs to run on a schedule |
| MCP | Needs external service integration |
Always pick the right tool for the job, not default to skills.
Behavior
Run through all 5 phases systematically.
Phase 1: Health Check
- Read
architecture.yaml - For each goal with a
health_check.command, run it and report pass/fail - For goals without health checks, check if
realized_bypoints to an existing file - Report:
[1/5] Health Check code_quality: ✅ healthy (tests passing) productivity: ⚠️ no health check defined ai_news: ○ not implemented yet
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 · 265 lines · 0 tokens per session scan A a67e672f3e99
hm-night is a command published in the GitHub repository JavanC/Homunculus (15 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,789 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 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.