skill: co-locate the pi-extensions agent skill in the package

Add skill/SKILL.md (+ skill/evaluate-extension-usage.py, referenced by the
skill via ./) so the canonical 'how to use fork/recall/ssh-controlmaster'
skill lives next to the extensions it documents — the single source of truth.

Motivation: the global AGENTS.md (pi-toolkit) tells every pi session to read
~/.agents/skills/pi-extensions/SKILL.md at session start to fix fork/recall
under-utilisation, but that skill previously lived ONLY in the private
skillset repo. In any environment without the skillset mounted (e.g. a
pi-devbox container started without it) the pointer dangled. Co-locating the
skill here gives a public, package-owned source that downstreams can vendor.

install.sh is intentionally unchanged: skill deployment on a normal
workstation stays the skillset repo's responsibility (no double-deploy).

skill/evaluate-extension-usage.py

@@ -0,0 +1,117 @@
+#!/usr/bin/env python3
+"""Evaluate pi-fork / pi-observational-memory usage from pi session transcripts.
+
+Mines pi's session .jsonl transcripts and reports:
+  - per-tool call counts (highlighting `fork` and `recall`)
+  - per-session fork/recall breakdown
+  - obsmem passive activity: compaction events, observations carried,
+    relevance-tier distribution, tokensBefore
+
+Works on any machine. Point it at one or more session roots; by default it
+scans ~/.pi/agent/sessions (the standard pi location, host or container).
+
+Usage:
+  ./evaluate-extension-usage.py                       # ~/.pi/agent/sessions
+  ./evaluate-extension-usage.py /path/to/sessions ... # explicit roots
+  ./evaluate-extension-usage.py --host HOST /path ... # label a root (for combined host+container runs)
+
+For a true host+container picture, run once per machine (or copy each
+machine's ~/.pi/agent/sessions here) and pass all roots together.
+"""
+import json, sys, os, glob, re, collections, argparse
+
+TIER_RE = re.compile(r'\[(low|medium|high|critical)\]')
+OBS_LINE_RE = re.compile(r'^\[[0-9a-f]{12}\] ', re.M)
+
+
+def walk_tools(x, counter):
+    if isinstance(x, dict):
+        tn = x.get("toolName")
+        if tn:
+            counter[tn] += 1
+        for v in x.values():
+            walk_tools(v, counter)
+    elif isinstance(x, list):
+        for v in x:
+            walk_tools(v, counter)
+
+
+def analyze(roots):
+    files = []
+    for r in roots:
+        if os.path.isfile(r) and r.endswith(".jsonl"):
+            files.append(r)
+        else:
+            files += glob.glob(os.path.join(r, "**", "*.jsonl"), recursive=True)
+    files = sorted(set(files))
+
+    tool_total = collections.Counter()
+    per_session = []
+    compactions = []
+    for f in files:
+        tc = collections.Counter()
+        with open(f, errors="ignore") as fh:
+            for ln in fh:
+                ln = ln.strip()
+                if not ln:
+                    continue
+                try:
+                    o = json.loads(ln)
+                except Exception:
+                    continue
+                walk_tools(o, tc)
+                if o.get("type") == "compaction":
+                    s = o.get("summary", "") or ""
+                    compactions.append({
+                        "file": os.path.basename(f),
+                        "tokensBefore": o.get("tokensBefore"),
+                        "observations": len(OBS_LINE_RE.findall(s)),
+                        "tiers": dict(collections.Counter(TIER_RE.findall(s))),
+                    })
+        tool_total.update(tc)
+        per_session.append((os.path.basename(f)[:10], tc.get("fork", 0),
+                            tc.get("recall", 0), sum(tc.values())))
+    return files, tool_total, per_session, compactions
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("roots", nargs="*",
+                    default=[os.path.expanduser("~/.pi/agent/sessions")])
+    args = ap.parse_args()
+
+    files, tool_total, per_session, comp = analyze(args.roots)
+    if not files:
+        print("No .jsonl transcripts found under:", args.roots, file=sys.stderr)
+        sys.exit(1)
+
+    print(f"=== {len(files)} transcripts under {args.roots} ===\n")
+    print("Tool call totals:")
+    for t, c in tool_total.most_common():
+        mark = "  <== pi-fork" if t == "fork" else ("  <== obsmem recall" if t == "recall" else "")
+        print(f"  {c:6d}  {t}{mark}")
+
+    fk = tool_total["fork"]; rc = tool_total["recall"]
+    fk_sess = sum(1 for p in per_session if p[1])
+    rc_sess = sum(1 for p in per_session if p[2])
+    print(f"\npi-fork:   {fk} calls across {fk_sess} sessions")
+    print(f"recall:    {rc} calls across {rc_sess} sessions"
+          + ("   (!) zero recall over the window — see SKILL.md calibration note" if rc == 0 else ""))
+
+    if comp:
+        tot_obs = sum(c["observations"] for c in comp)
+        tb = [c["tokensBefore"] for c in comp if c["tokensBefore"]]
+        print(f"\nobsmem passive: {len(comp)} compactions, {tot_obs} observations carried"
+              + (f", avg tokensBefore {sum(tb)//len(tb):,}" if tb else ""))
+        agg = collections.Counter()
+        for c in comp:
+            agg.update(c["tiers"])
+        if agg:
+            print("  relevance tiers:", dict(agg))
+    else:
+        print("\nobsmem passive: no compaction events found "
+              "(short sessions, or obsmem not active on these transcripts)")
+
+
+if __name__ == "__main__":
+    main()