evolve

A framework-update tool that brings lessons and preferences from a shared development knowledge repository into coding agents.

In plain words
What is it for?
Use it to preview or apply learned lessons, update agent rules, view statistics, and propagate changes to projects.
Why use it?
It reduces the need to apply the same lessons and rules manually across projects.

Skill for Claude CodeCodex

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 skills/samibs/skillfoundry/evolve
Any agent
npx skills add samibs/skillfoundry --skill evolve
Clone the repo
git clone --depth 1 https://github.com/samibs/skillfoundry

Made for: Claude Code, Codex.

Per session 12 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 596 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 $0.00012 $0.00596
Opus 5 $0.00006 $0.00298
Sonnet 5 $0.00002 $0.00119
Haiku 4.5 $0.00001 $0.00060

Measured 2d ago against content hash 846296e155c9, 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.

.agents/skills/evolve/SKILL.md · 100 lines

How it starts

The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/evolve - Framework Evolution from Dev-Memory

Bridge learned lessons from the dev-memory knowledge repository into claude_as framework agents.


Usage

/evolve                  Pull lessons and evolve agents
/evolve --dry-run        Show what would change
/evolve --commit         Evolve and auto-commit
/evolve --status         Show evolution statistics

Instructions

You are the Evolution Engine — the bridge between accumulated project knowledge and framework intelligence.

When invoked:

Step 1: Locate dev-memory

  • Check .claude/knowledge-sync.conf for DEV_MEMORY_DIR
  • Look in common locations (~/dev-memory, ~/projects/dev-memory)
  • If not found, guide user to clone it

Step 2: Run evolve.sh Execute the evolution script:

bash scripts/evolve.sh $ARGUMENTS

Step 3: Report results Show what was imported:

  • Lessons learned count
  • Anti-patterns imported
  • Tech stack preferences
  • Rules injected into _quality-primer.md

Step 4: Propagation guidance After evolution:

To propagate to all projects:
  ./update.sh <project-dir>

To propagate to all registered projects:
  ./update.sh --scan

What evolve.sh does:

  1. Reads dev-memory/global/lessons.jsonl — patterns promoted from 3+ occurrences
  2. Reads dev-memory/global/anti-patterns.jsonl — documented failures
  3. Reads dev-memory/global/tech-stack.jsonl — technology preferences
  4. Reads dev-memory/global/preferences.jsonl — developer preferences
  5. Generates agents/_learned-rules.md — full rule document for all agents
  6. Injects top rules into agents/_quality-primer.md "Learned Rules" section
  7. Optionally commits to claude_as repository

The Evolution Loop:

Project A (real work)
    ↓ knowledge-sync.sh
dev-memory (GitHub)
    ↓ evolve.sh          ← YOU ARE HERE
claude_as framework
    ↓ update.sh
All projects (improved agents)
    ↓ real work...
Project B learns from A's mistakes

Output Format:

Read the full file on GitHub · 100 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 · 100 lines · 12 tokens per session scan A 846296e155c9

Subscribe to this mod's changes

evolve is a skill published in the GitHub repository samibs/skillfoundry (12 stars, last pushed 1mo ago), licensed MIT. It adds 12 tokens to every session and 596 once invoked, about $0.0001 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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