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/kdevos12/alkyl/binding-kineticsnpx skills add Kdevos12/ALKYL --skill binding-kineticsgit clone --depth 1 https://github.com/Kdevos12/ALKYLWhat 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 | $0.00058 | $0.00820 |
| Opus 5 | $0.00029 | $0.00410 |
| Sonnet 5 | $0.00012 | $0.00164 |
| Haiku 4.5 | $0.00006 | $0.00082 |
Grade A, and why
binding-kinetics 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 2d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Binding Kinetics
Purpose
Analyze, predict, and optimize drug-target binding kinetics: on-rates (kon), off-rates (koff), residence time (RT = 1/koff), thermodynamic signatures (ΔH/ΔS), and structure-kinetics relationships (SKR).
When to Use This Skill
- Analyzing SPR sensorgrams (Biacore/Sierra)
- Fitting ITC thermograms for ΔH/ΔS/ΔG
- Computing residence time from MD simulations (τRAMD, metadynamics)
- Building QSAR models for koff/kon
- Interpreting kinetic selectivity vs equilibrium selectivity
- Prioritizing compounds by residence time, not just KD
Reference Files
| File | Content |
|---|---|
references/kinetics-theory.md |
kon/koff/KD/RT definitions, kinetic selectivity, two-state binding, conformational selection vs induced fit, thermodynamic signatures |
references/spr-analysis.md |
SPR sensorgrams, 1:1 Langmuir fitting, two-state model, Rmax/Rtheor, bulk correction, Biacore data parsing, Python fitting |
references/itc-analysis.md |
ITC thermogram integration, n/KD/ΔH/ΔS/ΔG fitting, SEDPHAT equivalents in Python, van't Hoff, enthalpy-entropy compensation |
references/residence-time-md.md |
τRAMD (random acceleration MD), funnel metadynamics, WTmetaD koff estimation, HTMD τRAMD Python, unbinding pathway analysis |
references/kinetic-qsar.md |
Structure-kinetics relationships (SKR), features for koff/kon models, kinetic maps (LE vs kinetic efficiency), koff cliff detection |
Quick Routing
"Fit my SPR data" → spr-analysis.md
"Fit my ITC experiment" → itc-analysis.md
"Compute residence time from MD" → residence-time-md.md
"Build a model to predict koff" → kinetic-qsar.md
"Why does my drug work despite poor KD?" → kinetics-theory.md
Key Relationships
# Core kinetic relationships
KD = koff / kon # M (equilibrium dissociation constant)
pKD = -log10(KD) # analogous to pIC50
RT = 1 / koff # seconds (residence time)
t_half = ln(2) / koff # seconds (half-life of complex)
# Thermodynamics
ΔG = RT_gas * ln(KD) # kcal/mol (RT_gas = 0.592 at 298K)
ΔG = ΔH - T*ΔS # enthalpy-entropy decomposition
# Typical drug ranges
# kon: 10^4 – 10^7 M^-1 s^-1
# koff: 10^-5 – 10^-1 s^-1
# KD: nM – µM
# RT: 10 s – 10^5 s (hours)
What ships with it
5 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.
- 2d ago First seen · 69 lines · 0 tokens per session scan A 516542ca6a5b
binding-kinetics is a skill published in the GitHub repository Kdevos12/ALKYL (6 stars, last pushed 5mo ago), licensed MIT. It adds 58 tokens to every session and 820 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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