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.
npx skills add s0912758806p/agentic-sop-to-work --skill second-opiniongit clone --depth 1 https://github.com/s0912758806p/agentic-sop-to-workWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/s0912758806p/agentic-sop-to-work/second-opinion)<a href="https://agentmods.dev/skills/s0912758806p/agentic-sop-to-work/second-opinion"><img src="https://agentmods.dev/badge/skills/s0912758806p/agentic-sop-to-work/second-opinion/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/s0912758806p/agentic-sop-to-work/second-opinion"><img src="https://agentmods.dev/badge/skills/s0912758806p/agentic-sop-to-work/second-opinion.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00266 | $0.00970 |
| Opus 5 | $0.00133 | $0.00485 |
| Sonnet 5 | $0.00053 | $0.00194 |
| Haiku 4.5 | $0.00027 | $0.00097 |
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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Second Opinion — adversarial honesty reviewer
An independent, skeptical second reader for a finished DRAFT. It checks whether every claim is backed by its evidence and hands back a findings report — which is itself a DRAFT. A human decides.
When to use / not use
- Use when: "get a second opinion on this report", "is this draft trustworthy / honest", "double-check the numbers before I sign", "red-team this output", "did it make anything up?"
- Not for architecture ("is my workflow decomposed / a mega-agent?") →
agentic-workflow-audit. - Not for source-code quality / bugs / security →
/code-review,/security-review. Second Opinion reads a produced artifact's claims vs its cited evidence, in any domain.
What it catches (domain-neutral)
- #1 wrong PASS/FAIL or spec-limit verdicts, and aggregates that don't recompute.
- #2 numbers with no matching source token (fabrication / transcription error).
- #3 invented identifiers / dates / names with no provenance (should be
【待補】). - #4 conclusions the data don't support (overreach) — advisory.
How it works (two layers; the guarantees are in CODE, not this prose)
- Deterministic layer (stdlib, hermetic): catches
#1/#2/#3. In FULL mode these are HARD at confidence 1.0 (the kittraceis authoritative); in DEGRADED mode they are SOFT at 0.5 (provenance reconstructed from supplied inputs). - Advisory LLM layer (you): catches
#4and fuzzy#1. It is capped (SECONDOP_MAX_LLM_PASSES, default 1) and every finding is clamped to SOFT / advisory / confidence ≤ 0.5, dropped unless it cites a verbatim draft span (orNO SOURCE), and suppressed if it re-litigates a slot the deterministic layer already settled.
To run it
Invoke the /second-opinion command, which orchestrates the deterministic pass → your
capped advisory pass → the code-enforced fold-in → the human STOP. Modes:
/second-opinion <run_dir>— FULL (an agentic-sop-kit run dir)/second-opinion <doc> --inputs <file...>— DEGRADED (any document)/second-opinion— the bundled cross-domain demo
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.
- 11d ago First seen · 48 lines · 266 tokens per session scan A b7be88c1c935
second-opinion is a skill published in the GitHub repository s0912758806p/agentic-sop-to-work (206 stars, last pushed 2d ago), licensed MIT. It adds 266 tokens to every session and 970 once invoked, about $0.0013 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
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A knowledge-capture tool that turns reusable bug explanations into a local RAG collection, meaning a searchable store of text that an agent can retrieve later. It records the trigger, incorrect implementation, correct implementation, and observable difference.
x-qdev
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x-cr
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x-spec2
A compact system-design guide for turning vague or cross-module requests into a small, structured specification package. It defines requirements, acceptance scenarios, module boundaries, and—when needed—data flow, state, timing, resources, or recovery design.
x-adversarial-risk
A focused adversarial review of a software specification. It tries to find small counterexamples that would expose incorrect implementations, such as invalid state changes, crashes, duplicate actions, permission mistakes, or concurrent events.
coordination-audit
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