self-improving-agent

name	self-improving-agent
description	Always-on lightweight observer. After EVERY user message, silently check: (1) did the user correct me or express a preference? (2) did the user express frustration about repetition? (3) is this a rule I've seen before in a different project? If ANY are true, run `uv run improve.py observe "<rule>" --project <name> [--domain <domain>]` to record it. Do NOT load the full skill for observation — this description is sufficient. Load the full SKILL.md body only when: checking escalation thresholds, writing to AGENTS.md, or running /improve. Manages ~/.agent-improvement/rules.yaml via improve.py CLI.
license	MIT

Self-Improving Agent

An always-on observer that captures user corrections and preferences, tracks repetition across projects, and escalates behavioral rules to the appropriate AGENTS.md file.

Two-Tier Activation

Tier 1: Observation (always in context)

The YAML description above is loaded every session. It contains everything needed for the lightweight per-message check:

1. After every user message, silently evaluate: did the user correct me, express a preference, or show frustration about repetition?
2. If yes, run one CLI command to record it.
3. Do NOT load the rest of this SKILL.md for observation alone.

Tier 2: Escalation & Writing (loaded on demand)

The sections below are loaded only when the agent needs to:

• Check escalation thresholds (/improve due)
• Write rules into AGENTS.md files
• Review the domain taxonomy or escalation logic
• Run /improve command

---

Observation Protocol

What to Capture

Record an observation when the user:

• Corrects the agent: "don't do X", "use Y instead", "that's wrong", "not like that"
• States a preference: "I prefer X", "always do Y", "from now on, Z"
• Expresses frustration about repetition: "again?", "I keep having to tell you", "every time", "I've said this before"
• Gives an explicit instruction: "remember this", "write that down", "note this"

What NOT to Capture

• One-time task instructions ("add a button here", "rename this variable")
• Clarification questions ("what did you mean by X?")
• Normal conversational flow
• Things already captured as identical rules

How to Record

uv run <skill-dir>/scripts/improve.py observe "<rule>" --project <name> [--domain <domain>] [--context "<what happened>"] [--explicit-scope global|local]

Rule phrasing: Write rules as imperatives. Bad: "user doesn't like pip". Good: "Use uv tool for Python CLI tools, never pip3 install".

Domain: Pick from the taxonomy below. If unsure, omit it (defaults to "unknown").

Explicit scope: Use --explicit-scope global when the user says "always", "everywhere", "in all projects". Use --explicit-scope local when the user says "in this project", "just here".

Project detection: If --project is omitted, the CLI auto-detects from git remote get-url origin.

---

Session Startup Protocol

At the start of each session, run:

uv run <skill-dir>/scripts/improve.py status

This loads all active rules into your context. Apply them during the session. Rules with written_to entries are confirmed — treat them as hard rules. Rules without are tentative — apply them but don't enforce rigidly.

---

Domain Taxonomy

Domains determine whether a rule should escalate to global or stay project-local.

General Domains (escalate to global when cross-project)

Domain	Examples
python-tooling	Package managers, virtualenvs, linting
git-practices	Commit messages, branching, PR conventions
security	Input validation, secret handling, permissions
code-style	Naming, formatting, comment style
error-handling	Try/catch patterns, error messages
testing	Test frameworks, coverage, test structure
documentation	Docstrings, README style, API docs
communication	Response length, tone, formatting
tool-usage	Which tools to use, search patterns
search-patterns	Grep vs glob, code navigation

Project-Specific Domains (stay local even when cross-project)

Domain	Examples
auth-architecture	Auth middleware, JWT patterns, session handling
import-patterns	Module structure, barrel exports, aliases
file-structure	Directory layout, naming conventions
api-design	REST patterns, endpoint naming, response format
database-queries	ORM patterns, migration style, query conventions
ui-components	Component patterns, state management, styling
config-management	Environment variables, config files, secrets
deployment	CI/CD, Docker, infrastructure

If a rule's domain is unknown, treat it as project-specific until the domain is identified.

---

Escalation Decision Tree

After recording an observation, the CLI prints the recommended action. The full logic:

IF explicit_scope == "global":
    → Write to global AGENTS.md immediately (any count)

ELSIF explicit_scope == "local":
    → Never escalate beyond project AGENTS.md (any count)
    → Write to project AGENTS.md at count >= 2

ELSIF total_count == 1:
    → Apply in-session only, no file write

ELSIF total_count >= 2 AND cross_project == false:
    → Write to project AGENTS.md

ELSIF total_count >= 2 AND cross_project == true AND domain is general:
    → Write to global AGENTS.md

ELSIF total_count >= 2 AND cross_project == true AND domain is project-specific:
    → Write to each affected project's local AGENTS.md

ELSIF domain == "unknown":
    → Treat as project-specific, do not escalate until domain is identified

Checking for Due Escalations

At session end (or when the user runs /improve):

uv run <skill-dir>/scripts/improve.py due

This shows all rules that have reached their escalation threshold but haven't been written yet.

Escalating

uv run <skill-dir>/scripts/improve.py escalate --dry-run

This prints exactly what should be written to which file. After reviewing, run without --dry-run to mark them as escalated in rules.yaml.

---

Writing Protocol

When a rule is ready for escalation, write it into the appropriate AGENTS.md file.

Where to Write

Scope	Path
Global	~/.config/opencode/AGENTS.md (or equivalent for the agent harness)
Local	<project-root>/AGENTS.md

How to Write

1. Read the existing AGENTS.md file
2. Find the appropriate section (or create one)
3. Add the rule as a concise bullet point — use the exact rule text from rules.yaml
4. Do NOT duplicate rules that already exist in the file
5. After writing, confirm:

uv run <skill-dir>/scripts/improve.py confirm <rule-id> --scope global|local

Formatting Rules in AGENTS.md

Write rules as concise, actionable instructions:

## Python Tool Management

- Use `uv tool` for installing Python CLI tools (never `pip3 install`).
- Use `uv run -- python -c "..."` for one-off Python commands (never `python3` or `python`).

Not like:

- The user has corrected me 3 times about pip. I should use uv instead.

---

Anti-Patterns

Over-Recording

Not every message is a correction. A user saying "try the other approach" is exploration, not a rule. Only record when the intent is clearly "do it this way from now on."

Premature Escalation

A rule said once is NOT a rule. Wait for repetition (count >= 2) unless the user explicitly says "always" or "everywhere."

Vague Rules

"I prefer clean code" is not actionable. Translate to specific behaviors: "Write functions under 20 lines. Extract helpers when logic exceeds 3 levels of nesting."

Conflicting Rules

If a new rule contradicts an existing one:

1. Record the new observation normally
2. Check which rule has more evidence (higher count, more recent)
3. If both are strong, ask the user which one to keep
4. Retire the loser by adding "retired": true to its entry in rules.yaml

Writing Without Confirming

Always run confirm after writing to AGENTS.md. Otherwise the system thinks the rule is still pending and will try to escalate it again.

---

CLI Reference

All commands use the improve.py script:

uv run <skill-dir>/scripts/improve.py <command>

Command	When	Purpose
observe <rule>	After user correction/preference	Record a new observation
status	Session start	Show all rules and counts
due	Session end or /improve	Show pending escalations
escalate [--dry-run]	When escalation is due	Mark rules for escalation
confirm <id> --scope	After writing to AGENTS.md	Mark rule as written
history <id>	Debugging	Full observation history
domains	Reference	List domain taxonomy
seed --from-agents-md	First-time setup	Import rules from existing AGENTS.md
init [--force]	First-time setup	Initialize rules.yaml

Path Resolution

The CLI is located at <skill-dir>/scripts/improve.py. The skill directory is:

• Local install: .claude/skills/self-improving-agent/scripts/improve.py
• Global install: ~/.claude/skills/self-improving-agent/scripts/improve.py
• OpenCode: ~/.config/opencode/skill/self-improving-agent/scripts/improve.py

If unsure, search for improve.py within the skill directory.

Data Location

All data is stored at ~/.agent-improvement/rules.yaml. Override with AGENT_IMPROVEMENT_HOME environment variable.

---

Complete Workflow Example

Session Start

$ uv run improve.py status
  use-uv-not-pip
    rule: Use uv tool for Python CLI tools, never pip3 install
    count: 3 (cross-project, domain=python-tooling [general])
    escalation: global, written_to: 1 files

  check-pyproject-first
    rule: Check pyproject.toml before assuming library availability
    count: 1 (single-project, domain=tool-usage [general])
    escalation: none, written_to: 0 files

During Session (Observation)

User says: "Stop using grep for finding files, use glob instead."

$ uv run improve.py observe "Use glob for file pattern matching, not grep" \
    --project my-app --domain search-patterns \
    --context "user corrected grep usage for file search"
RECORDED (count=1) → apply in-session only

Same correction in another project, next week:

$ uv run improve.py observe "Use glob for file pattern matching, not grep" \
    --project other-project --domain search-patterns \
    --context "user repeated same correction about grep vs glob"
RECORDED (count=2, cross-project, general domain) → candidate for GLOBAL AGENTS.md

Session End (Escalation)

$ uv run improve.py due
  use-glob-for-file-pattern-matching-not-grep
    rule: Use glob for file pattern matching, not grep
    count: 2, projects: my-app, other-project
    → ESCALATE TO: global AGENTS.md

Agent reads global AGENTS.md, adds the rule, then confirms:

$ uv run improve.py confirm use-glob-for-file-pattern-matching-not-grep --scope global
Confirmed: use-glob-for-file-pattern-matching-not-grep written to ~/.config/opencode/AGENTS.md