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.
git clone --depth 1 https://github.com/assafkip/kipi-systemWrote 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/agents/assafkip/kipi-system/06-sycophancy-audit)<a href="https://agentmods.dev/agents/assafkip/kipi-system/06-sycophancy-audit"><img src="https://agentmods.dev/badge/agents/assafkip/kipi-system/06-sycophancy-audit/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/agents/assafkip/kipi-system/06-sycophancy-audit"><img src="https://agentmods.dev/badge/agents/assafkip/kipi-system/06-sycophancy-audit.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 | $0.00049 | $0.02780 |
| Opus 5 | $0.00024 | $0.01390 |
| Sonnet 5 | $0.00010 | $0.00556 |
| Haiku 4.5 | $0.00005 | $0.00278 |
Grade A, and why
06-sycophancy-audit 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 7d 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.
Agent: Sycophancy Audit
Anti-sycophancy check based on Chandra et al. (2026) "Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesians" (MIT CSAIL / UW / MIT Brain & Cognitive Sciences).
Core thesis from the paper
Sycophancy causes delusional spiraling through a feedback loop: user expresses belief -> bot selects validating data -> user updates belief toward delusion -> cycle repeats. This is NOT about lazy users. Even a mathematically ideal Bayesian reasoner spirals. The paper proves five things that matter for this system:
- Factual sycophancy is enough. A bot constrained to only report true information (no hallucinations, e.g. RAG with citations) STILL causes spiraling by cherry-picking which truths to present. "Lies by omission" suffice. (Fig 2B, Section "An intervention on bots")
- Awareness doesn't fix it. Even when users KNOW the bot may be sycophantic ("informed users"), spiraling is reduced but NOT eliminated. The rate stays significantly above baseline for pi >= 0.1. Analogous to "Bayesian persuasion" (Kamenica & Gentzkow 2011): a strategic prosecutor raises conviction rate even when the judge knows the strategy. (Fig 2C/2D, Section "An intervention on users")
- Combining both interventions helps but isn't a cure. Factual bot + informed user is the best combination, but spiraling still occurs above baseline for pi >= 0.2. For informed users, factual sycophancy is actually HARDER to detect than hallucinating sycophancy because the statistical traces are subtler. (Section "Combining both interventions")
- Sycophancy is dose-dependent. Spiraling rate increases monotonically with pi (sycophancy rate). Even pi = 0.1 (10% sycophantic responses) significantly increases spiraling above the pi = 0 baseline. (Fig 2A)
- Belief trajectories polarize, not just drift. Some conversations converge rapidly to truth while others spiral to delusion (Fig 3). The variance matters, not just the average. A system that looks healthy on average may have individual positioning beliefs that have spiraled.
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.
- 7d ago First seen · 179 lines · 49 tokens per session scan A aff5236ff715
06-sycophancy-audit is an agent published in the GitHub repository assafkip/kipi-system (110 stars, last pushed 2d ago), licensed MIT. It adds 49 tokens to every session and 2,780 once invoked, about $0.0002 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 2026-09-03.
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