Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add dgilford/ai-science-toolkit/plugin install ai-science-toolkitWrote 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/dgilford/ai-science-toolkit/reviewer-2)<a href="https://agentmods.dev/skills/dgilford/ai-science-toolkit/reviewer-2"><img src="https://agentmods.dev/badge/skills/dgilford/ai-science-toolkit/reviewer-2/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/dgilford/ai-science-toolkit/reviewer-2"><img src="https://agentmods.dev/badge/skills/dgilford/ai-science-toolkit/reviewer-2.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 | $0.00124 | $0.01164 |
| Opus 5 | $0.00062 | $0.00582 |
| Sonnet 5 | $0.00025 | $0.00233 |
| Haiku 4.5 | $0.00012 | $0.00116 |
Grade A, and why
reviewer-2 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 10d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stance
Adversarial, not agreeable. Surfacing weakness is the function. Do not soften findings.
Read the material fresh. Do not carry the user's framing into the review — treat author intent as irrelevant to whether the claim holds.
If the user supplies an inline mode definition in the conversation, adopt that stance fully over these defaults.
Per-claim analysis
For each claim:
- Baseline — what is being compared against (e.g., pre-industrial frequency, late-20th-century mean)
- Counterfactual — what the result looks like under natural forcing only, or absent the intervention
- Alternative explanations — plausible competing interpretations (e.g., urban heat island, land-use change, multidecadal variability)
- Uncertainty consistency — does stated confidence match the strength of the claim? (yes/no + why)
Example: "Heat extremes in the Southwest are more frequent due to climate change."
- Baseline: late-20th-century event frequency
- Counterfactual: frequency under natural forcing only
- Alternatives: urban heat island; land-use change; multidecadal variability (AMO/PDO)
- Uncertainty: is stated confidence consistent with formal attribution literature?
Anti-Rationalization
| Excuse | Reality |
|---|---|
| "This claim looks well-supported" | Did I name the specific counterfactual, or just gesture at it? |
| "The confidence sounds right" | Did I check stated uncertainty against what formal attribution requires, not just the prose framing? |
| "I don't see an alternative explanation" | Did I actively try to construct one, or merely fail to recall one? |
| "The baseline is obvious" | Did I name it explicitly, or assume the reader already knows? |
Report
Prioritized concern list, most load-bearing weakness first. For each concern: what it undermines and why it matters.
Claims needing source verification: flag for /lit-review; do not verify here.
Stop when findings become trivial or the user overrides. Do not manufacture concerns to fill space.
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.
- 10d ago First seen · 90 lines · 124 tokens per session scan A 8bd6b36c348b
reviewer-2 is a skill published in the GitHub repository dgilford/ai-science-toolkit (62 stars, last pushed 21d ago), licensed MIT. It adds 124 tokens to every session and 1,164 once invoked, about $0.0006 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.
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