feat(ai): resolve Steam app IDs from the library, don't make the model guess — 0.29.0

The model guessed "Rainbow Six Siege" for appID 2694490 (Path of Exile 2). We
already know the names locally, so ground it: steam.appid_names() maps appid→name
from the scanned library, and ai.build_prompt scans the text for app IDs and
injects a resolved glossary. Only locally-known IDs are listed; no network, no
fine-tuning. Tests + verified live (2694490 = Path of Exile 2).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

src/rigdoctor/__init__.py

@@ -1,3 +1,3 @@
 """RigDoctor — modular hardware monitoring & crash diagnostics for Linux gamers."""
 
-__version__ = "0.28.1"
+__version__ = "0.29.0"

src/rigdoctor/core/ai.py

@@ -16,12 +16,15 @@ Answers are *grounded*: we pass the actual findings plus matched reference facts
 from __future__ import annotations
 
 import json
+import re
 import urllib.error
 import urllib.request
 
 from .. import config
 from . import ai_knowledge
 
+_APPID_RE = re.compile(r"\b\d{5,7}\b")  # Steam app IDs are 5–7 digits
+
 PROVIDERS = ("ollama", "claude")
 OLLAMA_DEFAULT_ENDPOINT = "http://localhost:11434"
 # Suggested Ollama model — strong instruction-following that fits an 8 GB GPU at Q4. Because we
@@ -89,10 +92,35 @@ def provider_label() -> str:
     return "not configured"
 
 
+def appid_glossary(text: str) -> str:
+    """Resolve Steam app IDs that appear in `text` against the user's scanned library.
+
+    We don't teach the model app IDs — we look them up locally and hand it the mapping, so it
+    names games correctly instead of guessing. Only IDs we can resolve are listed.
+    """
+    candidates = set(_APPID_RE.findall(text))
+    if not candidates:
+        return ""
+    try:
+        from . import steam
+        names = steam.appid_names()
+    except Exception:  # never let a glossary lookup break an explanation
+        return ""
+    known = sorted((i, names[i]) for i in candidates if i in names)
+    if not known:
+        return ""
+    return "App IDs (resolved from your installed games):\n" + "\n".join(
+        f"- {appid} = {name}" for appid, name in known)
+
+
 def build_prompt(findings_text: str) -> str:
-    """The user-message content: matched reference facts + the collected findings."""
-    facts = ai_knowledge.relevant(findings_text)
+    """The user-message content: app-ID glossary + matched reference facts + the findings."""
     parts = []
+    glossary = appid_glossary(findings_text)
+    if glossary:
+        parts.append(glossary)
+        parts.append("")
+    facts = ai_knowledge.relevant(findings_text)
     if facts:
         parts.append("Reference facts (use these to interpret the findings):")
         parts += [f"- {f}" for f in facts]

src/rigdoctor/core/steam.py

@@ -318,6 +318,11 @@ def cached_games() -> list[Game]:
     return [Game(**{k: g[k] for k in Game.__dataclass_fields__ if k in g}) for g in cache.get("games", [])]
 
 
+def appid_names() -> dict[str, str]:
+    """{appid: name} for the user's scanned games — lets us resolve IDs seen in logs (M14)."""
+    return {g.appid: g.name for g in cached_games() if g.appid and g.name}
+
+
 def rescan(cfg: dict | None = None) -> ScanResult:
     """Scan the selected libraries, diff against the cache, and persist the result.