chore: bump version to 1.0.0

.agent-plan.md

@@ -6,7 +6,7 @@
 
 ## Current System State
 
-**v0.5.0 in progress — Milestones 7–11 complete, v6 dataset shipped.** Full simulation engine + render/bundle + exposure filtering + CLI commands + validation harness implemented. v6 dataset adds: latent-aware touch intensity (`LatentDecayIntensity`), causally-grounded leakage trap (post-snapshot touches), student/instructor split, `touches_last_7_days` momentum feature, `acquisition_wave` cohort feature, soft ACV winsorization, GBM improvement validation.
+**v1.0.0 released (2026-05-02).** All milestones (M0–M13) complete. Package version bumped to 1.0.0 in pyproject.toml and leadforge/version.py. README updated with `pip install leadforge`. CHANGELOG consolidated under v1.0.0 heading.
 
 ---
 
@@ -154,6 +154,14 @@ Documentation + CI:
 - [x] `CHANGELOG.md` — created; covers v0.1.0 through post-v0.5.0 improvements; user-facing descriptions grouped by version
 - [x] `.agent-plan.md` — updated deferred items table
 
+### M15: Version bump to v1.0.0 (PR #47)
+
+- [x] `pyproject.toml` — version `0.1.0` → `1.0.0`, classifier `Pre-Alpha` → `Production/Stable`
+- [x] `leadforge/version.py` — `__version__` bumped to `1.0.0`
+- [x] `README.md` — install changed from `pip install git+...` to `pip install leadforge`; removed "PyPI coming" note
+- [x] `CHANGELOG.md` — `Unreleased` renamed to `v1.0.0 — (2026-05-02)`; milestone headings folded into collapsible development history
+- [x] `.agent-plan.md` — updated to reflect v1.0.0 release
+
 ### Fix: direct conversion bypass for pre-SQL leads (PR #45, closes #44)
 
 - [x] `leadforge/simulation/engine.py` — added `_DIRECT_CONVERSION_STAGES` and `_DIRECT_CONVERSION_DISCOUNT` (0.01) constants; pre-SQL leads (`mql`, `sal`) now have a small daily probability of converting directly, bypassing the full funnel
@@ -213,7 +221,7 @@ Documentation + CI:
 | M14: Notebook 2 (lead scoring baseline) | Deferred | v4 validation script covers this |
 | M14: Notebook 3 (public vs instructor) | Discarded | No current audience |
 | M14: Notebook 4 (recipe customization) | Discarded | Premature |
-| M15: Docs polish + v1.0 RC | **In progress** | README + CHANGELOG done; architecture diagram and notebooks remain |
+| M15: Docs polish + v1.0 release | **Done** | README, CHANGELOG, version bump to 1.0.0 complete; architecture diagram and notebooks remain post-v1 |
 
 ### From post-v1 list
 

CHANGELOG.md

@@ -7,23 +7,43 @@ Format inspired by [Keep a Changelog](https://keepachangelog.com/).
 
 ## Unreleased
 
+---
+
+## v1.0.0 — 2026-05-02
+
+First stable release. All milestones (M0–M13) complete.
+
+### Highlights
+
+- **Full end-to-end generation**: recipe → simulated world → relational bundle with deterministic reproducibility.
+- **90-day daily-step simulation engine** with churn, stage advancement, conversion hazards, and touch emission.
+- **5 motif families** (fit-dominant, intent-dominant, sales-execution-sensitive, demo/trial-mediated, buying-committee-friction) with stochastic rewiring.
+- **Exposure filtering**: `student_public` (leakage-safe) and `research_instructor` (full truth) modes.
+- **CLI**: `generate`, `inspect`, `validate`, `list-recipes` — all fully wired.
+- **Validation harness**: determinism, exposure monotonicity, realism bounds, difficulty profiles, cross-seed drift detection.
+- **v4–v6 dataset pipelines**: progressive dataset versions with leakage traps, student/instructor splits, value-aware scoring, and GBM improvement validation.
+
+### Post-milestone improvements (since M13)
+
 - **Direct conversion bypass** (PR #45): pre-SQL leads can now convert via a rare direct path, fixing the deterministic `is_sql → converts` invariant.
 - **Configurable label window** (PR #43): `label_window_days` controls conversion label derivation in the simulation.
 - **Generalized task support** (PR #40, #42): `primary_task` threaded through bundle, validation, and pipelines; dataset card prose adapts to non-conversion tasks.
 - **Pipeline extraction** (PR #29, #34): build pipeline functions extracted into `leadforge.pipelines` with proper RNG conventions.
 - **Latent-aware touch intensity** (PR #31): `LatentDecayIntensity` mechanism creates causal link between latent traits and touch patterns.
 - **Canonical validation module** (PR #26): reusable lead scoring validation with sklearn pipeline.
-- **v4–v6 dataset pipelines**: progressive dataset versions with leakage traps, student/instructor splits, value-aware scoring, and GBM improvement validation.
 
----
+### Development history
+
+<details>
+<summary>Milestone changelog (no intermediate versions were published)</summary>
 
-## Milestone 0.5.0 — Validation Harness & CLI Complete (2026-04-29)
+#### Milestone 0.5.0 — Validation Harness & CLI Complete (2026-04-29)
 
 - Full validation harness: determinism checks, exposure monotonicity, realism bounds, difficulty validation, cross-seed drift detection.
 - `leadforge validate` command with artifact checks, FK integrity, leakage detection, and task split validation.
 - Parquet metadata used for row counts (no full table reads during validation).
 
-## Milestone 0.4.0 — Simulation Engine & End-to-End Generation (2026-04-28)
+#### Milestone 0.4.0 — Simulation Engine & End-to-End Generation (2026-04-28)
 
 - 90-day daily-step simulation engine with churn, stage advancement, conversion hazards, and touch emission.
 - Population generation: accounts (3 latent traits), contacts (4 traits), leads (1 trait) with motif-family biases.
@@ -32,23 +52,25 @@ Format inspired by [Keep a Changelog](https://keepachangelog.com/).
 - CLI commands: `generate`, `inspect`, `validate`, `list-recipes` — all fully wired.
 - Bundle manifest with provenance, row counts, and SHA-256 file hashes.
 
-## Milestone 0.3.0 — World Structure & Mechanisms (2026-04-25)
+#### Milestone 0.3.0 — World Structure & Mechanisms (2026-04-25)
 
 - Hidden world graph (DAG) with 5 motif families: fit-dominant, intent-dominant, sales-execution-sensitive, demo/trial-mediated, buying-committee-friction.
 - Stochastic graph rewiring: optional-node dropping, edge-weight jitter, latent-confounder injection.
 - Mechanism layer: latent scores, conversion hazards, stage transitions, Poisson intensities, categorical influences, noisy proxies.
 - Motif-aware mechanism assignment policies.
 
-## Milestone 0.2.0 — Config, Recipes & Narrative (2026-04-20)
+#### Milestone 0.2.0 — Config, Recipes & Narrative (2026-04-20)
 
 - Typed `GenerationConfig`, `Recipe`, `WorldSpec` models with full precedence resolution (kwargs > override > recipe > defaults).
 - Seeded RNG with SHA-256-derived named substreams for reproducibility.
 - Narrative layer: company, product, market, GTM motion, personas, funnel stages — loaded from recipe YAML.
 - Schema layer: 9 entity dataclasses, 10 FK constraints, 29 snapshot features, feature dictionary writer.
 - Dataset card renderer from narrative + world spec.
 
-## Milestone 0.1.0 — Project Foundation (2026-04-18)
+#### Milestone 0.1.0 — Project Foundation (2026-04-18)
 
 - Package skeleton, CLI entry point (`leadforge list-recipes`), CI pipeline.
 - Recipe registry with `b2b_saas_procurement_v1` recipe.
 - GitHub Actions: lint, typecheck, test matrix (Python 3.11 + 3.12).
+
+</details>

README.md

@@ -11,10 +11,14 @@
 Requires **Python 3.11+**.
 
 ```bash
-pip install git+https://github.com/leadforge-dev/leadforge.git
+pip install leadforge
 ```
 
-> PyPI package coming with the v1.0 release.
+Or install directly from GitHub:
+
+```bash
+pip install git+https://github.com/leadforge-dev/leadforge.git
+```
 
 For development:
 

leadforge/version.py

@@ -1 +1,5 @@
-__version__ = "0.1.0"
+"""Single-source package version, read from installed metadata."""
+
+from importlib.metadata import version
+
+__version__: str = version("leadforge")

pyproject.toml

@@ -4,15 +4,15 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "leadforge"
-version = "0.1.0"
+version = "1.0.0"
 description = "Opinionated framework for generating synthetic CRM and GTM datasets from simulated commercial worlds"
 readme = "README.md"
 license = { text = "MIT" }
 requires-python = ">=3.11"
 authors = [{ name = "leadforge contributors" }]
 keywords = ["synthetic data", "CRM", "lead scoring", "machine learning", "simulation"]
 classifiers = [
-    "Development Status :: 2 - Pre-Alpha",
+    "Development Status :: 5 - Production/Stable",
     "Intended Audience :: Developers",
     "Intended Audience :: Education",
     "Intended Audience :: Science/Research",