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 5.5 | $0.00106 | $0.00388 |
| Sonnet 5.5 | $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 1mo 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.
- 1mo 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 (211 stars, last pushed 1mo ago), licensed MIT. It adds 266 tokens to every session and 970 once invoked, about $0.0011 per session on Opus 5.5. 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
state-management
Cache management, configuration best practices, and progressive disclosure patterns for efficient context window usage. Use when working with large responses, optimizing token costs, or managing plugin state across operations.
session-recap
Document Claude Code sessions by extracting knowledge into cross-referenced documentation. Triggers on "recap the session", "summarize the work", or after significant code changes.
kb-ingest
Ingest external sources into the knowledge bank through interactive study or quick filing. Two modes — Quick (summarize → file) and Study (theme-by-theme deep dive with online research and personal notes → multi-layer KB output → optional blog/slack synthesis). Triggers on "ingest this", "study this article", "add to…
kb-lint
Health-check the knowledge bank for orphan documents, stale content, broken WikiLinks, index drift, and missing frontmatter. Generates a severity-graded report. Use this skill whenever the user mentions lint, health check, KB maintenance, stale docs, broken links, orphan pages, missing references, knowledge bank…
x-bug2rag
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-tech-design
A technical-design document workflow that turns an approved feature specification into a separate architecture and implementation plan. It records modules, protocols, data flow, constraints, and test references for later task breakdown.