second-opinion

A review skill that asks independent reviewers to challenge an answer before it is shown to the user.

In plain words
What is it for?
Use it for second opinions, sanity checks, trade-off discussions, high-stakes choices, critiques, and devil's-advocate reviews.
Why use it?
It helps expose missed risks, weak assumptions, and alternative interpretations in important decisions or difficult problems.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/awrshift/agent-memory-kit/second-opinion
Any agent
npx skills add awrshift/agent-memory-kit --skill second-opinion
Clone the repo
git clone --depth 1 https://github.com/awrshift/agent-memory-kit

Made for: Claude Code, Codex.

Per session 130 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 933 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00130 $0.00933
Opus 5 $0.00065 $0.00466
Sonnet 5 $0.00026 $0.00187
Haiku 4.5 $0.00013 $0.00093

Measured 2d ago against content hash e028f81bb201, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

second-opinion scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to second-opinion — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/memory-kit/skills/second-opinion/SKILL.md · 71 lines

How it starts

The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Second Opinion — cross-check before you commit

Stress-test your own answer with reviewers who don't share your framing. The reviewer set depends on what you have available:

  • Always available: the isolated idea-validator agent (same model family, but NO parent context — it can't anchor on your framing, and it READS the actual files).
  • If you have access to a second model family (Gemini, GPT, …, via a CLI wrapper or API): add it as an external reviewer. A different training distribution catches different blind spots. It reviews from the brief only (no repo access) — lean on it for concept and tech-currency, not file-level facts.

When to invoke

  1. Two or more viable paths to choose between → Round-Table.
  2. High-stakes decision (architecture, launch copy, anything with real rollback cost) → Boardroom Debate.
  3. Stuck on the same problem after 2+ attempts, or a non-trivial proposal awaiting approval → Devil's Advocate.

If none fires, don't invoke — a single-model answer is enough for routine work. Out of scope: factual lookups ("what's the latest X") — that's WebSearch, not review.

Own thinking first (load-bearing)

Before ANY review style: do your own research, form your own proposal with rationale and trade-offs, show it to the user. Only then invoke reviewers to critique it. Asking a reviewer before forming your own position turns it into a seed for the decision instead of a validator — and a reviewer without your codebase context can confidently seed something wrong.

The three styles

1. Devil's Advocate (single critique)

Spawn idea-validator with a self-contained artifact (the design/decision/plan pasted inline, plus the file paths it should actually read). Or send the same artifact to your external model if the claim is about tech or the outside world.

2. Boardroom Debate (parallel validation — the headline pattern)

  1. Write ONE self-contained artifact. Paste content inline — never rely on file references a brief-only reviewer might silently fail to load.
  2. Launch ALL reviewers in the SAME message (parallel calls). Sequential calls destroy independence — a later reviewer sees the earlier one's framing.
  3. Build an acceptance ledger: | Concern | Reviewer A | Reviewer B | My evaluation | Action |
  4. Adjudicate, never count votes. All agreeing can share a blind spot; one dissenter with a file:line beats abstract agreement. A code-reading reviewer outranks a brief-only one on facts about the code. The procedure in full — the three acceptance layers and the claim→cheapest-decisive-check table — is reference/orchestrator-fact-check.md.
  5. Present the ledger critically: where you accept, where you push back, and why. You make the final call — reviewer output is INPUT, not the decision.

Read the full file on GitHub · 71 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 71 lines · 130 tokens per session scan A e028f81bb201

Subscribe to this mod's changes

second-opinion is a skill published in the GitHub repository awrshift/agent-memory-kit (31 stars, last pushed 2d ago), licensed MIT. It adds 130 tokens to every session and 933 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to second-opinion, differing in 0 lines, and is treated as a copy.

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