evolve

A command that reviews personal agent instincts—stored notes about recurring preferences or lessons—and routes each one to a hook, rule, script, agent, or skill.

In plain words
What is it for?
Use it to process instincts interactively or automatically, implement them according to their suggested mechanism, group skill-related instincts, and archive completed items.
Why use it?
It helps turn useful recurring behavior into the right kind of reusable implementation and archives instincts after they are covered.

Command

Install

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.

agentmods
npx agentmods add commands/javanc/homunculus/evolve
Clone the repo
git clone --depth 1 https://github.com/JavanC/Homunculus
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 937 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00937
Opus 5 $0.00000 $0.00468
Sonnet 5 $0.00000 $0.00187
Haiku 4.5 $0.00000 $0.00094

Measured 2d ago against content hash 7804e5e4ae4b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

evolve 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 2d 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.

commands/evolve.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/evolve — Route Instincts to Implementations

Analyze instincts and route each to the best implementation mechanism. Not everything becomes a skill.

Modes

  • Default → Interactive mode (manual confirmation)
  • --autoAuto mode (for nightly agent, no confirmation needed)

How It Works

Step 1: Route instincts with suggested_mechanism

Read all instincts from homunculus/instincts/personal/. For each instinct that has suggested_mechanism in its frontmatter:

suggested_mechanism Action
hook Implement as hook (add to .claude/settings.json) → archive instinct
rule Write .claude/rules/*.md → archive instinct
script Write to scripts/ → archive instinct
agent Write to homunculus/evolved/agents/ → archive instinct
skill Collect for skill aggregation (Step 2)

Archive = move from instincts/personal/ to instincts/archived/ with note:

_Archived: 2026-03-26 | Covered-by: hook:pre-commit.sh | Reason: implemented

Step 2: Aggregate remaining instincts into skills

For instincts without suggested_mechanism, or with suggested_mechanism: skill:

  1. Group by trigger/topic similarity
  2. 2+ instincts with similar triggers → Skill candidate
  3. High confidence (≥0.7) candidates auto-selected in --auto mode
  4. Generate skill to homunculus/evolved/skills/

Step 3: No tag? Use the Implementation Routing table

If an instinct has no suggested_mechanism, decide based on its nature:

  • Deterministic, every time? → Hook
  • Tied to specific files/paths? → Rule
  • Reusable knowledge collection? → Skill
  • Periodic automation? → Script + scheduler
  • Needs isolated AI context? → Agent

Interactive Mode

Present routing decisions for user confirmation:

Evolution Analysis
━━━━━━━━━━━━━━━━━━
Instincts: 12 total

Routing decisions:
  1. pre-commit-lint (confidence: 0.85) → hook (deterministic)
  2. error-log-patterns (confidence: 0.72) → rule (path-scoped)
  3. tdd-before-commit + test-first-workflow → skill (aggregate)

Select items to evolve (enter numbers) or 'all':

Read the full file on GitHub · 120 lines

Changes

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.

  1. 2d ago First seen · 120 lines · 0 tokens per session scan A 7804e5e4ae4b

Subscribe to this mod's changes

evolve 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 937 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.