Fix stale AI-facing docs: AGENTS.md v2 API, version drift, file casing

.claude/.codebase-info/.map-state.json

@@ -1,8 +1,8 @@
 {
   "tool": "codebase-mapper",
-  "version": "2.0.0",
-  "mappedAt": "2026-07-05",
-  "gitCommit": "28099f5aa6eccb491c66be4bcd22532f15bb407f",
+  "version": "2.8.0",
+  "mappedAt": "2026-07-18",
+  "gitCommit": "7e85456d9984483b29211bff1dd98820409e9635",
   "documents": [
     "architecture.md",
     "tech-landscape.md",
@@ -14,5 +14,18 @@
     "patterns.md",
     "coding-style.md",
     "onboarding.md"
-  ]
+  ],
+  "hashes": {
+    "INDEX.md": "17eaa0ba82f159465e126597aac349c6e4429330887b58742636734e15854313",
+    "architecture.md": "7c908f047e6b0f08824ccd7c3f674ad47bd547dde234d0bd424a6d2784c0cbb6",
+    "tech-landscape.md": "a9052f4bba3742e79556a49c888424e6d9de424970e9def440c7124f45ec6a41",
+    "directory-structure.md": "ecf7e3357b41a83e7f31e760db41ef0bcb4fdbc6f1d61bbb4daf896f425d6657",
+    "entry-points.md": "6bd4ccae3d975196e03fc2c4e86007eba89f1f6427232fd8adce78ec97d6b432",
+    "modules.md": "1238c76664edb1c1667fda23f39507bcab5b760b57a3a3728d7104b2cf8032e7",
+    "communication.md": "49741a7455b0f162881e1cfb2d797dc8e3832cc8782796bbcb8a10529f2c5a0b",
+    "dependencies.md": "b445a920c121e27006fec824add6865d01cf71212a517e5ff8b2058d3999037a",
+    "patterns.md": "12b96c2d4f8bc7507bcae39b2b385b9db4d0dec95ef6a2049958663aff021705",
+    "coding-style.md": "2f939544333b927cf8731f5bb906ce03cb3a46afa50c9735011ff8f7e4caca9e",
+    "onboarding.md": "3d28c671dc095a2aadb297bd7ab200c677779a99c7534e03e55a3d64c935f07e"
+  }
 }

.claude/.codebase-info/INDEX.md

@@ -1,14 +1,14 @@
 # Codebase Map — Atomic Agents
 
-*Last Updated: 2026-06-13*
+*Last Updated: 2026-07-18*
 
 Atomic Agents is a lightweight, modular Python framework for building agentic AI applications as
 composable, schema-driven building blocks (built on Instructor + Pydantic). This repository is a
 `uv`-workspace **monorepo**: the core framework, a TUI tool installer, a tool library, and examples.
 
 **Stack:** Python ≥3.12 · Instructor · Pydantic v2 · LiteLLM · MCP · Textual · uv + Hatchling
 **Shape:** Monorepo — `atomic-agents/` (core lib) · `atomic-assembler/` (CLI) · `atomic-forge/` (tools) · `atomic-examples/` (examples)
-**Package:** `atomic-agents` v2.8.1 on PyPI · core import package is `atomic_agents`
+**Package:** `atomic-agents` v2.9.1 on PyPI · core import package is `atomic_agents`
 
 ## Documents
 

.claude/.codebase-info/directory-structure.md

@@ -1,6 +1,6 @@
 # Directory Structure
 
-*Last Updated: 2026-07-05*
+*Last Updated: 2026-07-18*
 
 ## Root Layout
 
@@ -22,7 +22,7 @@ atomic-agents/                  # repo root (uv workspace)
 ├── atomic-examples/            # 16 runnable example apps (each its own project)
 ├── docs/                       # Sphinx + MyST documentation (api/, guides/, examples/)
 ├── guides/                     # DEV_GUIDE.md and contributor guides
-├── scripts/                    # sync_version.py, generate_llms_files.py
+├── scripts/                    # generate_llms_files.py (llms-*.txt bundles for the docs site)
 ├── pyproject.toml              # package metadata, deps, [tool.black], uv workspace
 ├── build_and_deploy.ps1        # version bump + uv build/publish
 ├── AGENTS.md                   # the project's own design philosophy (imported by CLAUDE.md)

.claude/.codebase-info/tech-landscape.md

@@ -1,6 +1,6 @@
 # Technology Landscape
 
-*Last Updated: 2026-06-13*
+*Last Updated: 2026-07-18*
 
 ## Source-of-Truth Files
 
@@ -38,8 +38,10 @@
   - `code-quality.yml` — on push/PR to `main`/`v2.0`: `uv sync`, `black --check`, `flake8`, then
     `pytest --cov=atomic_agents` across `atomic-agents`, `atomic-assembler`, `atomic-examples`,
     `atomic-forge`.
-  - `docs.yml` — on push to `main`: build Sphinx docs, run `scripts/sync_version.py` and
+  - `docs.yml` — on push to `main`: build Sphinx docs, run
     `scripts/generate_llms_files.py` (produces `llms-*.txt`), deploy to GitHub Pages.
+    The docs version needs no sync step — `docs/conf.py` reads it from the root
+    `pyproject.toml` via `tomllib`.
 - **Release:** `build_and_deploy.ps1 <major|minor|patch> [--dry]` bumps the version in
   `pyproject.toml`, then `uv sync` → `uv build` → `uv publish` (requires a `PYPI_TOKEN`).
 - **Distribution:** PyPI package `atomic-agents`; the `atomic` console script ships with it.

.github/workflows/docs.yml

@@ -38,10 +38,6 @@ jobs:
         run: |
           uv sync
 
-      - name: Sync version from pyproject.toml
-        run: |
-          uv run python scripts/sync_version.py
-
       - name: Build singlehtml for documentation extraction
         run: |
           cd docs

agents.md → AGENTS.md

@@ -40,19 +40,15 @@ atomic-monorepo/
 
 ### 1. atomic-agents/ - Core Framework
 
-**Published as:** `atomic-agents` on PyPI
-**Current Version:** 2.2.2
+**Published as:** `atomic-agents` on PyPI (version lives in the root `pyproject.toml`)
 **Purpose:** Main Python package containing all core framework components
 
 **Key Components:**
 - `agents/` - AtomicAgent class and agent configuration
-- `base/` - Base abstractions (BaseIOSchema, BaseTool, BasePrompt, BaseResource)
-- `context/` - Chat history and system prompt generation
+- `base/` - Base abstractions (BaseIOSchema, BaseTool, BaseToolConfig)
+- `context/` - ChatHistory, SystemPromptGenerator, dynamic context providers
 - `connectors/` - External integrations (MCP support)
-- `lib/` - Extended library components (components, factories, utils)
-- `memory/` - Memory management systems
-- `prompting/` - Prompt engineering utilities
-- `services/` - Service integrations
+- `utils/` - Shared utilities (token counting, formatting)
 
 **Installation:**
 ```bash
@@ -138,14 +134,18 @@ Every Atomic Agent consists of:
 All data flows through typed Pydantic schemas:
 
 ```python
-from atomic_agents.base import BaseIOSchema
+from atomic_agents import BaseIOSchema
 from pydantic import Field
 
 class CustomOutputSchema(BaseIOSchema):
+    """Response with follow-up suggestions."""
+
     chat_message: str = Field(..., description="The response message")
     suggested_questions: list[str] = Field(..., description="Follow-up questions")
 ```
 
+Every `BaseIOSchema` subclass requires a non-empty docstring — the framework enforces this at class-definition time, and the docstring plus field descriptions flow into the LLM prompt via Instructor.
+
 ### Composability Pattern
 
 Agents can be chained by connecting output schemas to input schemas:
@@ -161,15 +161,21 @@ This creates predictable data flow pipelines with type safety at each step.
 Dynamic context injection pattern allows runtime enhancement of prompts without modifying agent code:
 
 ```python
-context_provider = CustomContextProvider()
-agent = AtomicAgent(
-    system_prompt=prompt,
-    input_schema=InputSchema,
-    output_schema=OutputSchema,
-    context_providers=[context_provider]  # Inject runtime context
-)
+from atomic_agents.context import BaseDynamicContextProvider
+
+class SearchResultsProvider(BaseDynamicContextProvider):
+    def __init__(self, title: str):
+        super().__init__(title=title)
+        self.results: list[str] = []
+
+    def get_info(self) -> str:
+        return "\n".join(self.results)
+
+agent.register_context_provider("search_results", SearchResultsProvider("Search Results"))
 ```
 
+Providers can also be passed up front via `SystemPromptGenerator(context_providers={...})`. `get_info()` runs on every `agent.run()`, so keep it free of blocking I/O.
+
 ### Model Context Protocol (MCP)
 
 Full support for MCP enables connection to external tools and resources through standardized interfaces:
@@ -324,32 +330,46 @@ Recent improvements include:
 ## Quick Start
 
 ```python
-from atomic_agents import AtomicAgent
-from atomic_agents.base import BaseIOSchema
+import os
+
+import instructor
+import openai
 from pydantic import Field
 
-# Define schemas
+from atomic_agents import AgentConfig, AtomicAgent, BaseIOSchema
+from atomic_agents.context import ChatHistory, SystemPromptGenerator
+
 class InputSchema(BaseIOSchema):
+    """User's question for the agent."""
+
     query: str = Field(..., description="User's question")
 
 class OutputSchema(BaseIOSchema):
+    """Agent's answer with a confidence estimate."""
+
     answer: str = Field(..., description="Agent's response")
     confidence: float = Field(..., description="Confidence score 0-1")
 
-# Create agent
-agent = AtomicAgent(
-    system_prompt="You are a helpful assistant. Provide accurate answers.",
-    input_schema=InputSchema,
-    output_schema=OutputSchema,
-    model="gpt-5-mini",
+client = instructor.from_openai(openai.OpenAI(api_key=os.environ["OPENAI_API_KEY"]))
+
+agent = AtomicAgent[InputSchema, OutputSchema](
+    config=AgentConfig(
+        client=client,
+        model="gpt-5-mini",
+        history=ChatHistory(),
+        system_prompt_generator=SystemPromptGenerator(
+            background=["You are a helpful assistant. Provide accurate answers."],
+        ),
+    )
 )
 
-# Run agent
 result = agent.run(InputSchema(query="What is atomic computing?"))
 print(result.answer)
 print(f"Confidence: {result.confidence}")
 ```
 
+The type parameters on `AtomicAgent[In, Out]` carry runtime information (they drive Instructor's `response_model`), so write them explicitly and keep them accurate. The client must always be wrapped with Instructor — a raw provider SDK client will not enforce output schemas.
+
 ---
 
 ## Philosophy Summary

README.md

@@ -410,8 +410,6 @@ If you want to learn more about the motivation and philosophy behind Atomic Agen
 
 ## Star History
 
-## Star History
-
 <a href="https://www.star-history.com/?type=date&repos=eigenwise%2Fatomic-agents">
  <picture>
    <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/chart?repos=eigenwise/atomic-agents&type=date&theme=dark&legend=top-left&sealed_token=bLmINE964wFC41alauDl3hSyqW8sm5FyyW99qO_99iZLJ5RG_Mqygi8SrdMmVx06pCB-IdgNUbaiN_e57ToEL3XA1WAliiCjyA8TAgXAPUYsW1OPAJunEw" />

claude-plugin/atomic-agents/CHANGELOG.md

@@ -5,6 +5,27 @@ All notable changes to the Atomic Agents Claude Code Plugin will be documented i
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [Unreleased]
+
+### Changed
+
+- Rebranded BrainBlend → Eigenwise: marketplace name, URLs, and install docs now point at the `eigenwise` GitHub home. Install via `/plugin marketplace add eigenwise/atomic-agents`.
+- `new-app` MiniMax default model updated to MiniMax M3.
+
+### Fixed
+
+- Quoted `argument-hint` YAML values in skill frontmatter so GitHub Copilot CLI ≥1.0.65 loads all skills ([#265](https://github.com/eigenwise/atomic-agents/pull/265)).
+
+## [2.1.0] - 2026-04-29
+
+### Added
+
+- Four action-oriented creation skills: `create-atomic-schema`, `create-atomic-agent`, `create-atomic-tool`, `create-atomic-context-provider`. Each walks a clarify → write → verify → hand-off workflow for its component type, auto-triggering on the matching phrasing ("create a schema", "add a tool", ...). The `framework` skill and `new-app` scaffolder route to them instead of duplicating the material.
+
+### Fixed
+
+- `atomic-reviewer` no longer flags current-generation model names as errors.
+
 ## [2.0.1] - 2026-04-16
 
 Bug-fix release addressing two recurring false positives from `atomic-reviewer` reported in [issue #238](https://github.com/eigenwise/atomic-agents/issues/238).

docs/conf.py

@@ -1,13 +1,17 @@
 import os
 import sys
+import tomllib
+from pathlib import Path
 
 sys.path.insert(0, os.path.abspath(".."))
 
 project = "Atomic Agents"
 copyright = "2026, Kenny Vaneetvelde"
 author = "Kenny Vaneetvelde"
-version = "2.0.4"
-release = "2.0.4"
+
+with open(Path(__file__).resolve().parent.parent / "pyproject.toml", "rb") as f:
+    version = tomllib.load(f)["project"]["version"]
+release = version
 
 extensions = [
     "sphinx.ext.autodoc",