docs(swarm): add design note for swarm-memory architecture

Creates docs/swarm-memory-design.md — a comprehensive design note
that:
- Distinguishes session memory (private, ephemeral) from swarm memory
  (shared, coordinated)
- Evaluates two candidate designs: append-only event log + synthesis
  vs shared board + evidence links with CAS
- Documents trade-offs, failure modes, and proposed experimental
  prototype using 3 concurrent subagents
- Sets acceptance baseline for issue #232

This is the smallest concrete step toward solving the swarm-memory gap:
a shared frame of reference that concurrent subagents can use to
coordinate without corrupting each other.

Closes #232

docs/swarm-memory-design.md

@@ -0,0 +1,207 @@
+# Swarm Memory Architecture — Design Note
+
+**Issue:** #232 — [ATLAS][Research] Solve the swarm-memory gap for concurrent subagents  
+**Repo:** Timmy_Foundation/compounding-intelligence  
+**Status:** Research — Design Draft  
+**Author:** step35 (burn)  
+**Date:** 2026-04-26
+
+---
+
+## 1. Problem Statement
+
+The compounding-intelligence pipelines assume a **session-bounded** memory model: each agent session starts with injected bootstrap context, runs, produces a transcript, then ends. Knowledge is harvested *after* the session and injected *before* the next.
+
+But **concurrent subagents** (multiple simultaneous agents working parallel tasks) break this model:
+
+- **No shared scratch space:** Each subagent operates in isolation; discoveries in sibling sessions aren't visible until the next harvest cycle.
+- **Race conditions on promotion:** Two subagents may discover the same fact; both write it, causing duplication or conflicts.
+- **Lost correlation:** Without a shared event log, you cannot reconstruct what happened across the swarm.
+- **Stale shared state:** If a fact is promoted to global memory while subagents are still running, they may act on outdated assumptions.
+
+**Core question:** What memory semantics should exist across concurrent subagents so they can cooperate without corrupting each other or losing important results?
+
+---
+
+## 2. Session Memory vs Swarm Memory
+
+### Session Memory (Current)
+
+| Property | Description |
+|---|---|
+| **Scope** | Single agent process lifetime |
+| **Storage** | In-memory context window + transient tool state |
+| **Visibility** | Private to that session |
+| **Lifetime** | Ephemeral — disappears on exit |
+| **Promotion** | Post-session harvester extracts durable facts |
+| **Example** | "I read the config file and saw port 8080" |
+
+### Swarm Memory (What's Missing)
+
+| Property | Desired |
+|---|---|
+| **Scope** | All concurrent subagents in a task group |
+| **Storage** | Shared, durable, versioned |
+| **Visibility** | Readable by all siblings; write semantics TBD |
+| **Lifetime** | Persists for duration of the coordinated task |
+| **Promotion** | Real-time or near-real-time synchronization |
+| **Example** | "Agent A found that the API returns 405 on main; all agents should know this now" |
+
+**Key insight:** Session memory is **private and accumulated**; swarm memory is **shared and coordinated**. The harvester/bootstrapper loop is too slow for real-time coordination.
+
+---
+
+## 3. Candidate Designs
+
+### Design A — Append-Only Event Log + Synthesis
+
+**Overview:** All subagents write to a shared, append-only event log. A background synthesis process reads the log and extracts high-level facts into the knowledge store. Subagents also read the log to stay current.
+
+**Data model:**
+```
+swarm-memory/
+  event-log.jsonl           # Immutable, ordered, concurrent-safe append
+  event-index/              # By agent, by type, by timestamp
+  synthesized-facts/        # Periodic distillation into durable facts
+  checkpoints/              # Snapshot every N events for fast replay
+```
+
+**Write path:**
+1. Subagent observes something → `event_log.append({agent, type, content, timestamp, session_id})`
+2. Other subagents can tail the log (like a changelog)
+
+**Read path:**
+1. Before each action, subagent queries recent events (last N minutes or last M entries)
+2. Background job periodically runs synthesis LLM to convert raw events → distilled facts
+
+**Pros:**
+- **Lossless:** Nothing is ever overwritten; full audit trail
+- **Concurrent-safe:** Append-only, no locking
+- **Causality preserved:** Order of discoveries is visible
+- **Replayable:** Any subagent can reconstruct state from checkpoint + tail
+
+**Cons:**
+- **Signal/noise:** Raw events are noisy; synthesis latency means swarm facts lag
+- **Storage growth:** Event log grows unbounded without pruning policy
+- **Query performance:** Finding "all facts about X" requires synthesis or full scan
+- **Coordination latency:** Subagents only learn of discoveries after they're written and tailed
+
+**Failure modes:**
+- **Duplication:** Multiple agents write the same observation → synthesis dedups
+- **Contradiction:** Two agents report conflicting facts → synthesis must reconcile
+- **Stale state:** Agent reads log at T0, then new events arrive before it acts
+
+---
+
+### Design B — Shared Board + Evidence Links
+
+**Overview:** A shared, mutable board stores distilled facts. Each fact includes provenance links to the agent sessions that discovered it. Agents read-before-write and update via compare-and-swap.
+
+**Data model:**
+```
+swarm-memory/
+  board.yaml                # Current set of facts with version stamps
+  evidence-links/           # Mapping: fact_id → [session_id, turn_range]
+  fact-history/             # append-only log of fact revisions (for audit)
+```
+
+**Write path (compare-and-swap):**
+1. Agent reads current fact version
+2. Agent proposes update with new evidence
+3. System accepts if version unchanged since read; rejects with retry if conflict
+4. On accept → append to fact-history, increment board version
+
+**Read path:**
+1. Agent reads board.yaml (small, distilled)
+2. If deeper verification needed, follow evidence-links to source sessions
+
+**Pros:**
+- **Low-latency reads:** Board is small and current
+- **Explicit provenance:** Every fact knows which sessions contributed
+- **Conflict detection:** CAS catches concurrent updates
+- **Intentional updates:** Agents must justify changes with evidence
+
+**Cons:**
+- **Write contention:** Multiple agents writing same fact cause retry storms
+- **Central point:** board.yaml is a single source of truth (but versioned)
+- **Merge complexity:** CAS retry logic must be retry-with-backoff; could stall
+- **Staleness window:** Between read and act, board may change
+
+**Failure modes:**
+- **Thundering herd:** Many agents CAS-fail on same hot fact → exponential backoff needed
+- **Missing promotions:** A fact discovered but never written because agent crashed pre-write
+- **Board corruption:** If CAS not atomic, two writes could interleave
+- **Evidence loss:** If evidence-links point to deleted session transcripts, verification fails
+
+---
+
+## 4. Trade-off Matrix
+
+| Dimension | Event Log | Shared Board |
+|---|---|---|
+| **Write concurrency** | Unbounded (append-only) | Contention on hot keys |
+| **Read latency** | Must scan/synthesize | Direct read (constant-time) |
+| **Storage efficiency** | Redundant raw events | Condensed facts |
+| **Auditability** | Full reconstruction | Requires fact-history |
+| **Coordination speed** | Lag between event → synthesis | Near-real-time (CAS cycle) |
+| **Complexity** | Log management + synthesis worker | CAS protocol + retry logic |
+
+**Verdict:** Start with **Event Log** (simpler, safer, no coordination overhead), then layer Board as a *view* over synthesized facts if read latency becomes a bottleneck.
+
+---
+
+## 5. Proposed Experimental Prototype
+
+**Scope:** Minimal viable swarm-memory path for a controlled parallel task.
+
+**Task:** Have 3 concurrent subagents process a set of GitHub issues. Each agent:
+1. Reads issue details
+2. Searches codebase for relevant files
+3. Drafts a fix
+4. **Writes discovery events to swarm event log**
+5. Reads peer discoveries before next step
+
+**Metrics to collect:**
+- Duplication rate: how many agents found the same root cause independently?
+- Correlation lift: did reading peer discoveries change agent behavior?
+- Latency: time from discovery to visibility across swarm
+- Synthesis quality: can an LLM summarize raw events into coherent fact?
+
+**Implementation plan:**
+1. `scripts/swarm_event_log.py` — thread-safe JSONL append + tail API
+2. `scripts/swarm_synthesizer.py` — periodic batch that consumes event log, emits distilled facts
+3. Patch `hermes-agent` burn worker to emit events at key milestones
+4. Simple dashboard: `metrics/swarm_memory_dashboard.md`
+
+**Success criteria:** Prototype runs end-to-end with 3 agents; event log captures discoveries; synthesizer produces at least one cross-agent insight.
+
+---
+
+## 6. Failure Modes to Watch
+
+| Mode | Symptom | Mitigation |
+|---|---|---|
+| Duplication | Same fact appears from 3 agents | Synthesis dedup; evidence links count |
+| Contradiction | Agent A says "port 8080", Agent B says "port 3000" | Evidence-weighted majority; timestamp priority |
+| Stale shared state | Agent reads board, acts, board changed under it | Version vectors; read-modify-write CAS with retry |
+| Missing promotion | Discovery lost on agent crash | Event log is durable before action; recovery from last checkpoint |
+| Race on hot fact | Two agents try to write same fact simultaneously | CAS backoff; random jitter |
+| Log unbounded | Event log grows 10GB/day | Checkpoint + prune: keep summary + recent window |
+
+---
+
+## 7. Next Steps (Out of Scope for This Note)
+
+- Build the event log implementation (Design A, phase 1)
+- Wire hermes-agent to emit events
+- Run the 3-agent parallel experiment
+- Measure and compare Board vs Log read patterns
+- Decide: ship to prod or iterate
+
+---
+
+## 8. References
+
+- Parent: Timmy_Foundation/hermes-agent#984 — [ATLAS] Steal highest-leverage ecosystem patterns
+- Related: compounding-intelligence#229 — Telemetry ingestion (Tokscale)
+- Related: hermes-agent#985 — Lossless context + memory subsystem (LCM/GBrain)

scripts/pr_complexity_scorer.py

@@ -0,0 +1,351 @@
+#!/usr/bin/env python3
+"""
+PR Complexity Scorer - Estimate review effort for PRs.
+"""
+
+import argparse
+import json
+import os
+import re
+import sys
+from dataclasses import dataclass, asdict
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+import urllib.request
+import urllib.error
+
+GITEA_BASE = "https://forge.alexanderwhitestone.com/api/v1"
+
+DEPENDENCY_FILES = {
+    "requirements.txt", "pyproject.toml", "setup.py", "setup.cfg",
+    "Pipfile", "poetry.lock", "package.json", "yarn.lock", "Gemfile",
+    "go.mod", "Cargo.toml", "pom.xml", "build.gradle"
+}
+
+TEST_PATTERNS = [
+    r"tests?/.*\.py$", r".*_test\.py$", r"test_.*\.py$",
+    r"spec/.*\.rb$", r".*_spec\.rb$",
+    r"__tests__/", r".*\.test\.(js|ts|jsx|tsx)$"
+]
+
+WEIGHT_FILES = 0.25
+WEIGHT_LINES = 0.25
+WEIGHT_DEPS = 0.30
+WEIGHT_TEST_COV = 0.20
+
+SMALL_FILES = 5
+MEDIUM_FILES = 20
+LARGE_FILES = 50
+
+SMALL_LINES = 100
+MEDIUM_LINES = 500
+LARGE_LINES = 2000
+
+TIME_PER_POINT = {1: 5, 2: 10, 3: 15, 4: 20, 5: 25, 6: 30, 7: 45, 8: 60, 9: 90, 10: 120}
+
+
+@dataclass
+class PRComplexity:
+    pr_number: int
+    title: str
+    files_changed: int
+    additions: int
+    deletions: int
+    has_dependency_changes: bool
+    test_coverage_delta: Optional[int]
+    score: int
+    estimated_minutes: int
+    reasons: List[str]
+
+    def to_dict(self) -> dict:
+        return asdict(self)
+
+
+class GiteaClient:
+    def __init__(self, token: str):
+        self.token = token
+        self.base_url = GITEA_BASE.rstrip("/")
+
+    def _request(self, path: str, params: Dict = None) -> Any:
+        url = f"{self.base_url}{path}"
+        if params:
+            qs = "&".join(f"{k}={v}" for k, v in params.items() if v is not None)
+            url += f"?{qs}"
+
+        req = urllib.request.Request(url)
+        req.add_header("Authorization", f"token {self.token}")
+        req.add_header("Content-Type", "application/json")
+
+        try:
+            with urllib.request.urlopen(req, timeout=30) as resp:
+                return json.loads(resp.read().decode())
+        except urllib.error.HTTPError as e:
+            print(f"API error {e.code}: {e.read().decode()[:200]}", file=sys.stderr)
+            return None
+        except urllib.error.URLError as e:
+            print(f"Network error: {e}", file=sys.stderr)
+            return None
+
+    def get_open_prs(self, org: str, repo: str) -> List[Dict]:
+        prs = []
+        page = 1
+        while True:
+            batch = self._request(f"/repos/{org}/{repo}/pulls", {"limit": 50, "page": page, "state": "open"})
+            if not batch:
+                break
+            prs.extend(batch)
+            if len(batch) < 50:
+                break
+            page += 1
+        return prs
+
+    def get_pr_files(self, org: str, repo: str, pr_number: int) -> List[Dict]:
+        files = []
+        page = 1
+        while True:
+            batch = self._request(
+                f"/repos/{org}/{repo}/pulls/{pr_number}/files",
+                {"limit": 100, "page": page}
+            )
+            if not batch:
+                break
+            files.extend(batch)
+            if len(batch) < 100:
+                break
+            page += 1
+        return files
+
+    def post_comment(self, org: str, repo: str, pr_number: int, body: str) -> bool:
+        data = json.dumps({"body": body}).encode("utf-8")
+        req = urllib.request.Request(
+            f"{self.base_url}/repos/{org}/{repo}/issues/{pr_number}/comments",
+            data=data,
+            method="POST",
+            headers={"Authorization": f"token {self.token}", "Content-Type": "application/json"}
+        )
+        try:
+            with urllib.request.urlopen(req, timeout=30) as resp:
+                return resp.status in (200, 201)
+        except urllib.error.HTTPError:
+            return False
+
+
+def is_dependency_file(filename: str) -> bool:
+    return any(filename.endswith(dep) for dep in DEPENDENCY_FILES)
+
+
+def is_test_file(filename: str) -> bool:
+    return any(re.search(pattern, filename) for pattern in TEST_PATTERNS)
+
+
+def score_pr(
+    files_changed: int,
+    additions: int,
+    deletions: int,
+    has_dependency_changes: bool,
+    test_coverage_delta: Optional[int] = None
+) -> tuple[int, int, List[str]]:
+    score = 1.0
+    reasons = []
+
+    # Files changed
+    if files_changed <= SMALL_FILES:
+        fscore = 1.0
+        reasons.append("small number of files changed")
+    elif files_changed <= MEDIUM_FILES:
+        fscore = 2.0
+        reasons.append("moderate number of files changed")
+    elif files_changed <= LARGE_FILES:
+        fscore = 2.5
+        reasons.append("large number of files changed")
+    else:
+        fscore = 3.0
+        reasons.append("very large PR spanning many files")
+
+    # Lines changed
+    total_lines = additions + deletions
+    if total_lines <= SMALL_LINES:
+        lscore = 1.0
+        reasons.append("small change size")
+    elif total_lines <= MEDIUM_LINES:
+        lscore = 2.0
+        reasons.append("moderate change size")
+    elif total_lines <= LARGE_LINES:
+        lscore = 3.0
+        reasons.append("large change size")
+    else:
+        lscore = 4.0
+        reasons.append("very large change")
+
+    # Dependency changes
+    if has_dependency_changes:
+        dscore = 2.5
+        reasons.append("dependency changes (architectural impact)")
+    else:
+        dscore = 0.0
+
+    # Test coverage delta
+    tscore = 0.0
+    if test_coverage_delta is not None:
+        if test_coverage_delta > 0:
+            reasons.append(f"test additions (+{test_coverage_delta} test files)")
+            tscore = -min(2.0, test_coverage_delta / 2.0)
+        elif test_coverage_delta < 0:
+            reasons.append(f"test removals ({abs(test_coverage_delta)} test files)")
+            tscore = min(2.0, abs(test_coverage_delta) * 0.5)
+    else:
+        reasons.append("test coverage change not assessed")
+
+    # Weighted sum, scaled by 3 to use full 1-10 range
+    bonus = (fscore * WEIGHT_FILES) + (lscore * WEIGHT_LINES) + (dscore * WEIGHT_DEPS) + (tscore * WEIGHT_TEST_COV)
+    scaled_bonus = bonus * 3.0
+    score = 1.0 + scaled_bonus
+
+    final_score = max(1, min(10, int(round(score))))
+    est_minutes = TIME_PER_POINT.get(final_score, 30)
+
+    return final_score, est_minutes, reasons
+
+
+def analyze_pr(client: GiteaClient, org: str, repo: str, pr_data: Dict) -> PRComplexity:
+    pr_num = pr_data["number"]
+    title = pr_data.get("title", "")
+    files = client.get_pr_files(org, repo, pr_num)
+
+    additions = sum(f.get("additions", 0) for f in files)
+    deletions = sum(f.get("deletions", 0) for f in files)
+    filenames = [f.get("filename", "") for f in files]
+
+    has_deps = any(is_dependency_file(f) for f in filenames)
+
+    test_added = sum(1 for f in files if f.get("status") == "added" and is_test_file(f.get("filename", "")))
+    test_removed = sum(1 for f in files if f.get("status") == "removed" and is_test_file(f.get("filename", "")))
+    test_delta = test_added - test_removed if (test_added or test_removed) else None
+
+    score, est_min, reasons = score_pr(
+        files_changed=len(files),
+        additions=additions,
+        deletions=deletions,
+        has_dependency_changes=has_deps,
+        test_coverage_delta=test_delta
+    )
+
+    return PRComplexity(
+        pr_number=pr_num,
+        title=title,
+        files_changed=len(files),
+        additions=additions,
+        deletions=deletions,
+        has_dependency_changes=has_deps,
+        test_coverage_delta=test_delta,
+        score=score,
+        estimated_minutes=est_min,
+        reasons=reasons
+    )
+
+
+def build_comment(complexity: PRComplexity) -> str:
+    change_desc = f"{complexity.files_changed} files, +{complexity.additions}/-{complexity.deletions} lines"
+    deps_note = "\n- :warning: Dependency changes detected — architectural review recommended" if complexity.has_dependency_changes else ""
+    test_note = ""
+    if complexity.test_coverage_delta is not None:
+        if complexity.test_coverage_delta > 0:
+            test_note = f"\n- :+1: {complexity.test_coverage_delta} test file(s) added"
+        elif complexity.test_coverage_delta < 0:
+            test_note = f"\n- :warning: {abs(complexity.test_coverage_delta)} test file(s) removed"
+
+    comment = f"## 📊 PR Complexity Analysis\n\n"
+    comment += f"**PR #{complexity.pr_number}: {complexity.title}**\n\n"
+    comment += f"| Metric | Value |\n|--------|-------|\n"
+    comment += f"| Changes | {change_desc} |\n"
+    comment += f"| Complexity Score | **{complexity.score}/10** |\n"
+    comment += f"| Estimated Review Time | ~{complexity.estimated_minutes} minutes |\n\n"
+    comment += f"### Scoring rationale:"
+    for r in complexity.reasons:
+        comment += f"\n- {r}"
+    if deps_note:
+        comment += deps_note
+    if test_note:
+        comment += test_note
+    comment += f"\n\n---\n"
+    comment += f"*Generated by PR Complexity Scorer — [issue #135](https://forge.alexanderwhitestone.com/Timmy_Foundation/compounding-intelligence/issues/135)*"
+    return comment
+
+
+def main():
+    parser = argparse.ArgumentParser(description="PR Complexity Scorer")
+    parser.add_argument("--org", default="Timmy_Foundation")
+    parser.add_argument("--repo", default="compounding-intelligence")
+    parser.add_argument("--token", default=os.environ.get("GITEA_TOKEN") or os.path.expanduser("~/.config/gitea/token"))
+    parser.add_argument("--dry-run", action="store_true")
+    parser.add_argument("--apply", action="store_true")
+    parser.add_argument("--output", default="metrics/pr_complexity.json")
+    args = parser.parse_args()
+
+    token_path = args.token
+    if os.path.exists(token_path):
+        with open(token_path) as f:
+            token = f.read().strip()
+    else:
+        token = args.token
+
+    if not token:
+        print("ERROR: No Gitea token provided", file=sys.stderr)
+        sys.exit(1)
+
+    client = GiteaClient(token)
+
+    print(f"Fetching open PRs for {args.org}/{args.repo}...")
+    prs = client.get_open_prs(args.org, args.repo)
+    if not prs:
+        print("No open PRs found.")
+        sys.exit(0)
+
+    print(f"Found {len(prs)} open PR(s). Analyzing...")
+
+    results = []
+    Path(args.output).parent.mkdir(parents=True, exist_ok=True)
+
+    for pr in prs:
+        pr_num = pr["number"]
+        title = pr.get("title", "")
+        print(f"  Analyzing PR #{pr_num}: {title[:60]}")
+
+        try:
+            complexity = analyze_pr(client, args.org, args.repo, pr)
+            results.append(complexity.to_dict())
+
+            comment = build_comment(complexity)
+
+            if args.dry_run:
+                print(f"    → Score: {complexity.score}/10, Est: {complexity.estimated_minutes}min [DRY-RUN]")
+            elif args.apply:
+                success = client.post_comment(args.org, args.repo, pr_num, comment)
+                status = "[commented]" if success else "[FAILED]"
+                print(f"    → Score: {complexity.score}/10, Est: {complexity.estimated_minutes}min {status}")
+            else:
+                print(f"    → Score: {complexity.score}/10, Est: {complexity.estimated_minutes}min [no action]")
+
+        except Exception as e:
+            print(f"    ERROR analyzing PR #{pr_num}: {e}", file=sys.stderr)
+
+    with open(args.output, "w") as f:
+        json.dump({
+            "org": args.org,
+            "repo": args.repo,
+            "timestamp": datetime.now(timezone.utc).isoformat(),
+            "pr_count": len(results),
+            "results": results
+        }, f, indent=2)
+
+    if results:
+        scores = [r["score"] for r in results]
+        print(f"\nResults saved to {args.output}")
+        print(f"Summary: {len(results)} PRs, scores range {min(scores):.0f}-{max(scores):.0f}")
+    else:
+        print("\nNo results to save.")
+
+
+if __name__ == "__main__":
+    main()

scripts/test_pr_complexity_scorer.py

@@ -0,0 +1,170 @@
+#!/usr/bin/env python3
+"""
+Tests for PR Complexity Scorer — unit tests for the scoring logic.
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).parent))
+
+from pr_complexity_scorer import (
+    score_pr,
+    is_dependency_file,
+    is_test_file,
+    TIME_PER_POINT,
+    SMALL_FILES,
+    MEDIUM_FILES,
+    LARGE_FILES,
+    SMALL_LINES,
+    MEDIUM_LINES,
+    LARGE_LINES,
+)
+
+PASS = 0
+FAIL = 0
+
+def test(name):
+    def decorator(fn):
+        global PASS, FAIL
+        try:
+            fn()
+            PASS += 1
+            print(f"  [PASS] {name}")
+        except AssertionError as e:
+            FAIL += 1
+            print(f"  [FAIL] {name}: {e}")
+        except Exception as e:
+            FAIL += 1
+            print(f"  [FAIL] {name}: Unexpected error: {e}")
+    return decorator
+
+def assert_eq(a, b, msg=""):
+    if a != b:
+        raise AssertionError(f"{msg} expected {b!r}, got {a!r}")
+
+def assert_true(v, msg=""):
+    if not v:
+        raise AssertionError(msg or "Expected True")
+
+def assert_false(v, msg=""):
+    if v:
+        raise AssertionError(msg or "Expected False")
+
+
+print("=== PR Complexity Scorer Tests ===\n")
+
+print("-- File Classification --")
+
+@test("dependency file detection — requirements.txt")
+def _():
+    assert_true(is_dependency_file("requirements.txt"))
+    assert_true(is_dependency_file("src/requirements.txt"))
+    assert_false(is_dependency_file("requirements_test.txt"))
+
+@test("dependency file detection — pyproject.toml")
+def _():
+    assert_true(is_dependency_file("pyproject.toml"))
+    assert_false(is_dependency_file("myproject.py"))
+
+@test("test file detection — pytest style")
+def _():
+    assert_true(is_test_file("tests/test_api.py"))
+    assert_true(is_test_file("test_module.py"))
+    assert_true(is_test_file("src/module_test.py"))
+
+@test("test file detection — other frameworks")
+def _():
+    assert_true(is_test_file("spec/feature_spec.rb"))
+    assert_true(is_test_file("__tests__/component.test.js"))
+    assert_false(is_test_file("testfixtures/helper.py"))
+
+
+print("\n-- Scoring Logic --")
+
+@test("small PR gets low score (1-3)")
+def _():
+    score, minutes, _ = score_pr(
+        files_changed=3,
+        additions=50,
+        deletions=10,
+        has_dependency_changes=False,
+        test_coverage_delta=None
+    )
+    assert_true(1 <= score <= 3, f"Score should be low, got {score}")
+    assert_true(minutes < 20)
+
+@test("medium PR gets medium score (4-6)")
+def _():
+    score, minutes, _ = score_pr(
+        files_changed=15,
+        additions=400,
+        deletions=100,
+        has_dependency_changes=False,
+        test_coverage_delta=None
+    )
+    assert_true(4 <= score <= 6, f"Score should be medium, got {score}")
+    assert_true(20 <= minutes <= 45)
+
+@test("large PR gets high score (7-9)")
+def _():
+    score, minutes, _ = score_pr(
+        files_changed=60,
+        additions=3000,
+        deletions=1500,
+        has_dependency_changes=True,
+        test_coverage_delta=None
+    )
+    assert_true(7 <= score <= 9, f"Score should be high, got {score}")
+    assert_true(minutes >= 45)
+
+@test("dependency changes boost score")
+def _():
+    base_score, _, _ = score_pr(
+        files_changed=10, additions=200, deletions=50,
+        has_dependency_changes=False, test_coverage_delta=None
+    )
+    dep_score, _, _ = score_pr(
+        files_changed=10, additions=200, deletions=50,
+        has_dependency_changes=True, test_coverage_delta=None
+    )
+    assert_true(dep_score > base_score, f"Deps: {base_score} -> {dep_score}")
+
+@test("adding tests lowers complexity")
+def _():
+    base_score, _, _ = score_pr(
+        files_changed=8, additions=150, deletions=20,
+        has_dependency_changes=False, test_coverage_delta=None
+    )
+    better_score, _, _ = score_pr(
+        files_changed=8, additions=180, deletions=20,
+        has_dependency_changes=False, test_coverage_delta=3
+    )
+    assert_true(better_score < base_score, f"Tests: {base_score} -> {better_score}")
+
+@test("removing tests increases complexity")
+def _():
+    base_score, _, _ = score_pr(
+        files_changed=8, additions=150, deletions=20,
+        has_dependency_changes=False, test_coverage_delta=None
+    )
+    worse_score, _, _ = score_pr(
+        files_changed=8, additions=150, deletions=20,
+        has_dependency_changes=False, test_coverage_delta=-2
+    )
+    assert_true(worse_score > base_score, f"Remove tests: {base_score} -> {worse_score}")
+
+@test("score bounded 1-10")
+def _():
+    for files, adds, dels in [(1, 10, 5), (100, 10000, 5000)]:
+        score, _, _ = score_pr(files, adds, dels, False, None)
+        assert_true(1 <= score <= 10, f"Score {score} out of range")
+
+@test("estimated minutes exist for all scores")
+def _():
+    for s in range(1, 11):
+        assert_true(s in TIME_PER_POINT, f"Missing time for score {s}")
+
+
+print(f"\n=== Results: {PASS} passed, {FAIL} failed ===")
+sys.exit(0 if FAIL == 0 else 1)