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 vasilyu1983/AI-Agents-public --skill foundations-control-theorygit clone --depth 1 https://github.com/vasilyu1983/AI-Agents-publicWrote 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/vasilyu1983/ai-agents-public/foundations-control-theory)<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/foundations-control-theory"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/foundations-control-theory/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/vasilyu1983/ai-agents-public/foundations-control-theory"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/foundations-control-theory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 77 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
- medium Excessive Agency · line 343 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00045 | $0.08136 |
| Opus 5 | $0.00023 | $0.04068 |
| Sonnet 5 | $0.00009 | $0.01627 |
| Haiku 4.5 | $0.00005 | $0.00814 |
Grade A, and why
foundations-control-theory 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 9d 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 — 354 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Control Theory Foundations
12 applied control-theory primitives for feedback control and dynamical systems, backed by a formal theory map. Each primitive owns a specific failure mode in any system that must reach and hold a target state despite disturbances, delays, noise, or nonlinearities. Primitives are domain-agnostic: the same PID loop that controls CPU utilization controls budget pacing and retry rates; the same circuit breaker that isolates a failing database isolates a failing LLM tool.
Contents
- Quick Reference
- Primitive Index
- Formal Supporting Theory
- Anti-Patterns
- Misuse Boundaries
- Expert Judgment
- Decision Checklist
- Composition Recipes
- Workflow
- ASCII Flow
- Navigation
- Fact-Checking
Quick Reference
| Primitive | Problem It Solves | Key Parameters |
|---|---|---|
| PID Control | Drive output to setpoint despite steady-state error and disturbances | Kp, Ki, Kd; tuned via Ziegler-Nichols |
| Feedback vs. Feedforward | Reactive-only loops ignore predictable disturbances | Plant model accuracy; disturbance measurability |
| Observability & Controllability | States you cannot see or reach make the loop fail silently | Controllability matrix rank; observability matrix rank |
| Lyapunov Stability | No proof that a loop converges; may oscillate or diverge | Lyapunov function V(x); dV/dt < 0 condition |
| MPC | One-step control ignores future constraints and couplings | Horizon N; cost matrices Q, R; constraint bounds |
| Kalman Filter | Noisy measurements degrade controller and monitoring accuracy | Process noise Q; measurement noise R; model (A, B, C) |
| Dead-Time Compensation | Transport lag causes oscillation or instability | Dead time L; plant model (delay-free) |
| Anti-Windup | Integrator saturates during limit-clamping → overshoot on release | Actuator min/max; tracking constant T_t |
| Gain Scheduling | Single fixed-gain controller fails across operating regimes | Scheduling variable σ; per-regime gain tables |
| Circuit Breaker & Backpressure | Cascading failure; unbounded queue growth | Failure threshold; timeout; half-open probe logic |
| Rate Limiting / Token Bucket | Bursts and retry storms overload downstream; 429s cascade | Fill rate r; burst capacity b; per-request cost s |
| DeePC / Behavioral Systems | MPC without a plant model — unknown dynamics make model-based prediction impossible | Hankel matrix T (data length); regularization λ_g, λ_y; persistency-of-excitation order |
What ships with it
20 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.
- agents/openai.yaml 382 B
- assets/templates/control-theory/01-pid-control.md 3.5 KB
- assets/templates/control-theory/02-feedback-vs-feedforward.md 3.8 KB
- assets/templates/control-theory/03-observability-controllability.md 3.9 KB
- assets/templates/control-theory/04-lyapunov-stability.md 4.8 KB
- assets/templates/control-theory/05-mpc.md 5.8 KB
- assets/templates/control-theory/06-kalman-filter.md 4.4 KB
- assets/templates/control-theory/07-dead-time-compensation.md 4.5 KB
- assets/templates/control-theory/08-anti-windup.md 4.2 KB
- assets/templates/control-theory/09-gain-scheduling.md 4.3 KB
- assets/templates/control-theory/10-circuit-breaker-backpressure.md 4.9 KB
- assets/templates/control-theory/11-rate-limiting-token-bucket.md 4.8 KB
- assets/templates/control-theory/12-deepc-behavioral.md 6.4 KB
- assets/templates/control-theory/README.md 6.9 KB
- data/sources.json 17 KB
- learnings.consolidated.md 602 B
- learnings.md 988 B
- references/formal-theory-map.md 4.3 KB
- references/patterns-scenarios-traps.md 3.6 KB
- references/primitives-overview.md 8.7 KB
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.
- 9d ago First seen · 354 lines · 45 tokens per session scan A a339e7b066b8
foundations-control-theory is a skill published in the GitHub repository vasilyu1983/AI-Agents-public (87 stars, last pushed 10d ago), licensed MIT. It adds 45 tokens to every session and 8,136 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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