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 skloxo/TideTrading --skill performance-attributiongit clone --depth 1 https://github.com/skloxo/TideTradingWrote 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/skloxo/tidetrading/performance-attribution)<a href="https://agentmods.dev/skills/skloxo/tidetrading/performance-attribution"><img src="https://agentmods.dev/badge/skills/skloxo/tidetrading/performance-attribution.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 5.1 | $0.00032 | $0.02420 |
| Opus 5 | $0.00016 | $0.01210 |
| Sonnet 5 | $0.00006 | $0.00484 |
| Haiku 4.5 | $0.00003 | $0.00242 |
Grade A, and why
performance-attribution 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 6d 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 — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Attribution Analysis
Overview
Decompose portfolio excess returns into explainable sources: sector allocation, stock selection, factor exposure, timing contribution, and more. This helps explain why a strategy made or lost money, rather than only how much it made or lost.
Brinson Attribution Model
Single-Period Brinson-Fachler Model
Total excess return = portfolio return - benchmark return
Decomposed into three parts:
1. Allocation effect: sector-weight deviation × sector benchmark return deviation
2. Selection effect: stock selection within a sector × sector benchmark weight
3. Interaction effect: weight deviation × stock-selection deviation
Mathematical formulas:
Let w_p,i = portfolio weight of sector i
w_b,i = benchmark weight of sector i
r_p,i = portfolio return of sector i
r_b,i = benchmark return of sector i
R_b = total benchmark return
Allocation_i = (w_p,i - w_b,i) × (r_b,i - R_b)
Selection_i = w_b,i × (r_p,i - r_b,i)
Interaction_i = (w_p,i - w_b,i) × (r_p,i - r_b,i)
Total excess = Σ(Allocation_i) + Σ(Selection_i) + Σ(Interaction_i)
Example Brinson Attribution
### Brinson Sector Attribution
| Sector | Portfolio Weight | Benchmark Weight | Portfolio Return | Benchmark Return | Allocation | Selection | Interaction |
|------|---------|---------|---------|---------|---------|---------|---------|
| Food & Beverage | 20% | 10% | 15% | 8% | +0.3% | +0.7% | +0.7% |
| Electronics | 15% | 12% | 5% | 10% | -0.1% | -0.6% | +0.2% |
| Banks | 5% | 20% | 3% | 2% | +0.3% | +0.2% | -0.2% |
| Others | 60% | 58% | 8% | 7% | +0.0% | +0.6% | +0.0% |
| **Total** | 100% | 100% | 9.5% | 6.2% | **+0.5%** | **+0.9%** | **+0.7%** |
Excess return 3.3% = allocation effect 0.5% + selection effect 0.9% + interaction effect 0.7% + residual 0.2%
Multi-Period Attribution (Linked Brinson)
Directly summing single-period attribution creates residuals (compounding effect). Common approaches:
Method 1: arithmetic linking (simple sum of each period's attribution)
- Advantage: simple
- Disadvantage: residual remains
Method 2: Carino logarithmic linking
- Advantage: no residual
- Disadvantage: more complex
Practical recommendation: arithmetic linking is enough for monthly attribution; residuals are usually <0.1%
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.
- 6d ago First seen · 255 lines · 32 tokens per session scan A 434df366d1ed
performance-attribution is a skill published in the GitHub repository skloxo/TideTrading (10 stars, last pushed 2d ago), licensed MIT. It adds 32 tokens to every session and 2,420 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 2026-08-31.
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