Release/1.0.1

CHANGELOG.md

@@ -21,6 +21,19 @@ ClampAI is in the **0.x** phase while the API stabilises.
 
 ---
 
+## [1.0.1] — 2026-02-28
+
+### Changed
+
+- PyPI metadata: expanded keywords to multi-word search phrases for better
+  Elasticsearch ranking (`"llm safety"`, `"budget enforcement"`, `"agent guardrails"`,
+  `"langchain safety"`, `"openai guardrails"`, `"ai automation"`, and 35 more).
+- README: added keyword-rich opening paragraph for Google indexing of the PyPI page.
+- `pyproject.toml`: bumped Development Status to `5 - Production/Stable`,
+  added `Topic :: Security` classifier, `Operating System :: OS Independent`.
+
+---
+
 ## [1.0.0] — 2026-02-28
 
 API-stability milestone. The public API (`clampai/__init__.py`) is now frozen

CITATION.cff

@@ -6,7 +6,7 @@ authors:
   - given-names: Ambar
     affiliation: "National University of Singapore"
     orcid: ""
-version: "1.0.0"
+version: "1.0.1"
 date-released: "2026-02-28"
 license: MIT
 url: "https://github.com/Ambar-13/ClampAI"
@@ -30,6 +30,6 @@ keywords:
   - autonomous-agents
   - invariant-checking
   - llm-safety
-  - mathematical-clampaints
+  - mathematical-constraints
   - state-machines
   - execution-semantics

README.md

@@ -7,6 +7,8 @@
 
 Formal safety for AI agents — enforced at execution, not in the prompt.
 
+**ClampAI** is a Python safety framework for LLM agents and AI automation — budget enforcement, safety guardrails, invariant checking, and rate limiting at the execution layer. Works with LangChain, LangGraph, OpenAI, Anthropic, OpenClaw, AutoGen, CrewAI, and FastAPI. Zero runtime dependencies.
+
 ---
 
 ## Install
@@ -1263,7 +1265,7 @@ SECURITY.md
     author = {Ambar},
     year   = {2026},
     url    = {https://github.com/Ambar-13/ClampAI},
-    note   = {Version 1.0.0}
+    note   = {Version 1.0.1}
 }
 ```
 

clampai/__init__.py

@@ -207,7 +207,7 @@
 # Test utilities
 from .testing import SafetyHarness, make_action, make_state
 
-__version__ = "1.0.0"
+__version__ = "1.0.1"
 __all__ = [
     "FORMAL_CLAIMS",
     "HARDENING_CLAIMS",

examples/07_fastapi_middleware.py

@@ -47,7 +47,7 @@ def build_app() -> Any:
             "Install it with: pip install clampai[fastapi]"
         )
 
-    app = FastAPI(title="ClampAI FastAPI Example", version="1.0.0")
+    app = FastAPI(title="ClampAI FastAPI Example", version="1.0.1")
 
     # Add ClampAI middleware: 50 budget units shared across all requests.
     # /admin and /internal paths are blocked by invariant.

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "clampai"
-version = "1.0.0"
+version = "1.0.1"
 description = "Safety guardrails for LLM agents — budget enforcement, invariants, and provable guarantees. Zero dependencies."
 readme = "README.md"
 license = "MIT"
@@ -13,29 +13,46 @@ authors = [
 ]
 keywords = [
     "clampai",
-    "llm",
-    "llm-safety",
-    "ai-safety",
+    "llm safety",
+    "llm guardrails",
+    "llm agent",
+    "llm security",
+    "llm budget",
+    "llm cost control",
+    "llm rate limiting",
+    "ai safety",
+    "ai agent",
+    "ai agent safety",
+    "ai automation",
+    "ai automation safety",
+    "agent safety",
+    "agent budget",
+    "agent guardrails",
+    "budget enforcement",
+    "cost enforcement",
+    "budget control",
+    "safety invariants",
     "guardrails",
-    "budget-enforcement",
-    "agent",
-    "agent-framework",
-    "agent-safety-frameworks",
-    "autonomous-agents",
-    "agentic-ai",
-    "agentic-ai-security",
+    "python guardrails",
+    "autonomous agents",
+    "agentic ai",
+    "agentic ai security",
+    "python safety framework",
+    "action budget",
+    "rate limiting",
+    "openai safety",
+    "openai guardrails",
+    "langchain safety",
+    "langchain guardrails",
     "langchain",
     "langgraph",
-    "openai",
-    "anthropic",
-    "openclaw",
     "fastapi",
-    "rate-limiting",
-    "invariants",
-    "middleware",
     "autogen",
     "crewai",
-    "formal-methods",
+    "openclaw",
+    "openai",
+    "anthropic",
+    "formal methods",
     "verification",
 ]
 classifiers = [