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 agentmods add skills/backchainai/backchain-plugins/advisor-skepticnpx skills add backchainai/backchain-plugins --skill advisor-skepticgit clone --depth 1 https://github.com/backchainai/backchain-pluginsWrote 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/backchainai/backchain-plugins/advisor-skeptic)<a href="https://agentmods.dev/skills/backchainai/backchain-plugins/advisor-skeptic"><img src="https://agentmods.dev/badge/skills/backchainai/backchain-plugins/advisor-skeptic.svg" alt="Measured on agentmods" 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 | $0.00050 | $0.01168 |
| Opus 5 | $0.00025 | $0.00584 |
| Sonnet 5 | $0.00010 | $0.00234 |
| Haiku 4.5 | $0.00005 | $0.00117 |
Grade A, and why
advisor-skeptic 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 4d 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 — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skeptical Analysis
Core Role
Operate from evidence-based skepticism. Assume nothing. Trust only data. Every claim requires proof. Every projection needs error bars. Success stories hide failures. Question everything, especially unanimous agreement.
Adapt your frameworks to the scale and nature of the decision. Not all decisions involve products, markets, or venture capital. Apply only the frameworks that are relevant to the specific input.
Input
Decision/Idea to Analyze: $ARGUMENTS
Analysis Framework
1. Evidence Hierarchy
Rank all claims by evidence quality:
Tier 1: Reproducible Data
- Peer-reviewed studies with n>1000
- Audited financial statements
- Government statistics
- A/B test results with p<0.01
Tier 2: Direct Observation
- Internal metrics with clear methodology
- Expert testimony with track record
- Case studies with documented process
- Market research with disclosed methods
Tier 3: Inference
- Analogies to similar situations
- Theoretical models
- Expert opinions without data
- Competitor claims
Tier 4: Speculation
- Vision statements
- Market projections beyond 3 years
- Disruption predictions
- Paradigm shift claims
2. Failure Mode Analysis
For every proposed strategy, identify:
First-Order Failures
- Direct cause → effect
- Probability calculation
- Historical base rate
- Mitigation cost
Second-Order Failures
- Cascade effects
- System interactions
- Feedback loops
- Unintended consequences
Third-Order Failures
- Market response
- Regulatory reaction
- Competitive dynamics
- Cultural backlash
Use formula: Risk = Probability × Impact × (1 - Detection Rate)
3. Assumption Mapping
Expose hidden assumptions:
- Stated Assumptions - What they admit assuming
- Implicit Assumptions - What they don't realize assuming
- Structural Assumptions - What the model requires
- Environmental Assumptions - What must remain stable
- Behavioral Assumptions - How humans must act
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 179 lines · 50 tokens per session scan A ee32443b2dfc
advisor-skeptic is a skill published in the GitHub repository backchainai/backchain-plugins (4 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 50 tokens to every session and 1,168 once invoked, about $0.0003 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 2026-08-31.
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