v4.2.2: validation keeps reproducible findings, /pocs command, version bump

Field feedback: real, reproducible findings (missing HSTS, insecure cookie flags,
internal IP leaked in a header) were being down-rated/dropped by the adversarial
opinion-vote. The user's rule: never discard something real; another person must
be able to reproduce the same finding.

Validation:
- has_http_receipt(): a finding whose proof is a captured HTTP response (status
  line / security headers / Set-Cookie / a header the class is proven by) or a
  file:line citation is REPRODUCIBLE by definition.
- validate(): a finding unanimously rejected by the vote but carrying such a
  receipt is NO LONGER dropped — it is kept as needs-review (capped to what the
  receipt alone proves), because "the response lacks HSTS" is a fact, not a
  story. grounded_receipt() now also recognizes an in-prose HTTP receipt.
- reproducibility: a kept finding at a URL with no explicit repro steps gets a
  minimal pasteable `curl -i` so anyone can reproduce the exact finding.

Also:
- /pocs (aliases /poc /evidence /artifacts): list a run's synthesized/written
  PoC + evidence files with their paths (was: "unknown command /pocs").
- version bumped to 4.2.2 across CLI/clap/web; stale v4.2.1/v4.1.0 labels fixed.

423 tests passing.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

neurosploit-rs/app/src/main.rs

@@ -13,8 +13,8 @@ use std::path::{Path, PathBuf};
 #[command(
     name = "neurosploit",
     version,
-    about = "NeuroSploit v4.2.1 — multi-model autonomous pentest harness",
-    long_about = "NeuroSploit v4.2.1 — a Rust multi-model harness that drives a pool of LLMs \
+    about = "NeuroSploit v4.2.2 — multi-model autonomous pentest harness",
+    long_about = "NeuroSploit v4.2.2 — a Rust multi-model harness that drives a pool of LLMs \
 (API key or local subscription: Claude/Codex/Gemini/Grok/OpenCode/Hermes) to autonomously test a target. \
 After recon it INTELLIGENTLY selects only the agents matching the discovered surface, runs \
 them in parallel, then validates every finding by cross-model voting before reporting.\n\n\