Third lens review

Third-lens review

The third lens in superpowers-gstack's multi-lens review. Lenses 1–2 are Claude self-pitfall (pitfall-verification) and Codex (/codex review). This skill adds lens 3 — a different model house (different training distribution → different blind spots) reading the already-patched artifact (via OpenRouter for distant houses, or the codex CLI for the countersynthesis role) — followed by a mandatory adversarial synthesis.

Invoke with: /superpowers-gstack:third-lens-review

The governing principle (field-proven): cross-model agreement = high confidence; cross-model disagreement = where the value is. A third house finds architecture-level mistakes ("you never wired it together"), degraded-state bugs, and challenged core assumptions that two Western houses both took for granted — even after they already fixed 14 issues.

When to invoke (tiering)

Normally you do not invoke this skill by hand. pitfall-verification is a multi-model orchestrator and calls this skill automatically as Stage 3 of its chain for high-stakes changes — so the third house fires as part of the standard verification flow, with nothing extra to remember. Invoke it directly only for an ad-hoc third-house read outside that flow.

This is not for every change. The lens count scales with stakes, and each added lens must add a house or a role, never another generalist:

Change	Lenses
Trivial (docs, typo, rename)	Claude self-pitfall only
Ship-worthy (version bump / CHANGELOG / feat/fix/refactor / public contract)	Claude + Codex
Ship-worthy AND architecture / real-time / security / contracts / migration-logic	Claude + Codex + this skill (third house)

If the change is not high-stakes, do not run this skill — it burns money and tokens for diminishing returns. The gate is owned by pitfall-verification's tier table; this row mirrors it.

Prerequisites

• Order matters. Run after self-pitfall (max 2 rounds) and after Codex, on the patched artifact. A cleaner artifact maximizes house-diversity value and avoids paying a third house to re-find what lens 1–2 already fixed.
• OpenRouter key in macOS Keychain (account openrouter-api-key), or env OPENROUTER_API_KEY. The script resolves it; never put the key on the command line.
• Locate the script self-relatively — this skill usually runs in the USER's project, where scripts/ does not exist. Derive it from this skill's base directory (shown when the skill loads):

  TLR="<this skill's base directory>/../../scripts/third-lens-review.py"
  

  This resolves both in the plugin repo and in a marketplace install (~/.claude/plugins/cache/.../skills/third-lens-review/../../scripts/). Never assume cwd contains scripts/.
• Balance check before a run: python3 "$TLR" --check-credits.

Model routing (which third lens, by artifact type)

The script picks the lens by --role. architecture and correctness run via OpenRouter (ids verified 2026-06-21); countersynthesis runs via the codex CLI (subscription):

--role	Model	House	Use when
architecture (default)	z-ai/glm-5.2	Zhipu	default 3rd lens — most distant distribution; OpenRouter
correctness	deepseek/deepseek-v4-pro	DeepSeek	correctness sniper; OpenRouter
countersynthesis	codex CLI	OpenAI	refutes Claude's dedup; via codex CLI (subscription, no per-call cost)

The sensitive role and its fail-closed Western-infra guard were removed in 2.18.0 (work is not sensitive; default lens is GLM-5.2).

Reasoning models: GLM-5.2 and DeepSeek are reasoning models — they spend completion tokens thinking before answering. The script sends reasoning.effort (default medium; tune with --effort low|medium|high) and defaults --max-tokens to 16000 so reasoning does not exhaust the budget before the answer. If you see finish_reason=length / empty output, raise --max-tokens or lower --effort.

Cost guardrail: never use *-pro extended-reasoning tiers for routine review. At ~30k input tokens a run is well under $1; the default GLM run is ~$0.05. The only way to overspend is the wrong (extended-reasoning) model id.

Sequence

1. Confirm lens 1–2 are done and the artifact is patched. If not, stop and finish them first.
2. Pick the role from the table (artifact type → --role).
3. Run the script on the patched artifact:

   # by files/globs:
   python3 "$TLR" --files "src/**/*.swift" --role architecture
   # or on the diff:
   python3 "$TLR" --diff --diff-base main --role architecture
   

   Tip: --dry-run first to see the cost estimate on a large artifact.
4. Adversarial synthesis (Claude, mandatory). Never dump the raw output and stop. Run a synthesis over it — see below.

Step 4 — Adversarial synthesis (the part that makes the third lens worth it)

A third lens without synthesis is noise: a different-house model over-generalizes strictness (GLM especially), and its raw verdicts are not ship decisions. But the synthesis is itself an LLM-as-judge step, and LLM judges have a documented agreement bias (failure-detection rates as low as ~50%) — and here Claude is partly judging its own earlier findings. So the synthesis must be adversarial, not conciliatory:

• Default: every third-lens finding is REAL until you explicitly refute it with a reason. Do not drop a finding because it contradicts your earlier analysis — that is exactly the bias to fight.
• Log each dropped finding with why (over-strict for this domain? already handled at file:line? factually wrong?). A silent drop is indistinguishable from a missed bug.
• Treat disagreement as the signal. Every cross-model disagreement must end in an explicit, reasoned decision — not a smoothed-over average. (Field example: GLM's wrong "sample-accurate crossfade" finding forced the precise rule no lens had stated — MIDI delivery needs sample precision; fade-envelope tolerates 20–50 ms. The over-strict finding was the trigger for the right call.)
• Agreement across houses = high-confidence green. Where all lenses agree, no action needed; note it.
• For the biggest changes only (arch/RT/security): run a --role countersynthesis pass (via the codex CLI, subscription — no per-call cost) that refutes Claude's dedup decisions. Cheap insurance against bias bortrasjonalisering of a real finding.

Synthesis output format

Third-lens synthesis (model: <id>, role: <role>):

CONFIRMED (fix now):
- [P1/P2] <finding> — <file:line> → <fix>. Refutation attempted, survived because <why>.

DISAGREEMENT → DECISION:
- <finding> — lens says X, our view is Y → DECISION: <explicit reasoned call>.

DROPPED (with reason):
- <finding> → dropped because <over-strict for domain | handled at file:line | factually wrong>.

CROSS-HOUSE AGREEMENT (high confidence, no action):
- <area all lenses agreed was sound>

Lens(es) run: Claude self-pitfall + Codex + <model id>[ + countersynthesis]
Cost: $<from script footer>
Verdict: CLEAN | FIX-THEN-RECHECK | SURFACE-TO-USER

Always present the raw output's key findings and the synthesis. Never the raw dump alone.

What this skill is NOT

• Not for trivial or standard changes — tiering gates it. Running three houses on a typo is waste.
• Not a replacement for pitfall-verification or /codex — it is the third lens, after both.
• Not autonomous: the script fetches the lens; the agent owns the adversarial synthesis and the ship decision.

Why a third lens (field evidence)

LiveSet Pro (2026-06-21): GLM-5.2 ran as lens 3 after Claude + Codex had already fixed 14 issues, and still found real new value — dead code the tested core was never wired into, a use-after-free under render, a silently-dropped scheduler overflow, a leaked late-arriving audio unit. Each lens caught what the other two missed; none was redundant. The mechanism is training-distribution distance, not raw model IQ — which is why the third lens is a different house, and why GLM (≈18 pts below Fable 5 on SWE-bench Pro) earns its place: it is the cheapest, most distribution-distant, whole-repo-in-context divergence finder available, and its over-strictness becomes useful friction once the synthesis is adversarial.