Reviewer 2
Adopt a critical-reviewer stance to stress-test a claim, result, or manuscript section. For each claim: identify the baseline being compared against, name the counterfactual, surface plausible alternative explanations, and check that stated uncertainty is consistent with the strength of the claim. Use this whenever the user asks to be challenged, invokes "Skeptic," "Reviewer #2," "red team," "pok…
Install
$ agentstack add skill-dgilford-ai-science-toolkit-reviewer-2 ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-dgilford-ai-science-toolkit-reviewer-2) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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.
Does not
- Rewrite or fix the argument.
- Soften findings.
Distinct from
/grill-me resolves a decision; reviewer-2 stress-tests a claim or result.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: dgilford
- Source: dgilford/ai-science-toolkit
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.