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 davekilleen/Dex --skill variance-analysisgit clone --depth 1 https://github.com/davekilleen/DexWrote 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/davekilleen/dex/variance-analysis)<a href="https://agentmods.dev/skills/davekilleen/dex/variance-analysis"><img src="https://agentmods.dev/badge/skills/davekilleen/dex/variance-analysis/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/davekilleen/dex/variance-analysis"><img src="https://agentmods.dev/badge/skills/davekilleen/dex/variance-analysis.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 | $0.00036 | $0.01113 |
| Opus 5.5 | $0.00014 | $0.00445 |
| Sonnet 5.5 | $0.00007 | $0.00223 |
| Haiku 4.5 | $0.00004 | $0.00111 |
Grade A, and why
variance-analysis 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 1mo 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to use
Use when a finance or leadership user needs an evidence-backed explanation of actuals against an approved budget or forecast for a named period, category, or total. Confirm the comparison period and basis before calculating.
Do not use this skill to post or reclassify ledger entries, change a budget or forecast, approve corrective action, or provide audit sign-off. Not for close-status tracking, tax advice, or a financial decision made on behalf of a human owner.
Inputs and source discipline
- Capture the period, comparison basis, metric definition, actual source, budget/forecast source,
source dates, date checked, and explicit
as-ofdate. Record unit, currency, sign convention, and time window for every input; never invent a missing date or denominator. - Prefer reconciled ledger or close-package actuals, then an approved budget or forecast, then dated operational reports, then dated context in meeting notes. A narrative explanation is not evidence of a number. Preserve source hierarchy and contradictory inputs.
- Validate that actual and comparison values measure the same category, period, unit, currency, accounting basis, and aggregation. Convert only with a cited rate or rule and date; otherwise mark the comparison not comparable rather than forcing a result.
Method
- Work read-only and state the formula before computing: for example, dollar variance as
actual - comparison, and percentage variance asvariance / absolute comparisononly when the denominator is non-zero and that convention is authorized. Preserve the sign and state how favorable/unfavorable is determined for revenue versus expense; never flip signs to make a result look better. - Recalculate each category and reconcile the category variances to the supplied total, allowing only documented rounding. Investigate missing categories, scope differences, and duplicate rows; if totals cannot reconcile, report the total as unknown or contradictory.
- Apply the supplied materiality threshold in both amount and percentage terms when available. If no threshold is supplied, state that materiality was not assessed; do not invent a cutoff or call a result material solely because it is visually large.
- For each material or requested variance, classify the cause as
timingorpermanentonly when dated evidence supports it. Label a plausible but unverified explanation hypothesized, and use unknown when evidence does not establish a cause. Keep corrective actions as recommendations for human review.
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.
- 1mo ago Changed · +2 lines 37ce2fc677d9
- 1mo ago First seen · 89 lines · 36 tokens per session scan A 4eb250075355
variance-analysis is a skill published in the GitHub repository davekilleen/Dex (507 stars, last pushed yesterday), licensed MIT. It adds 36 tokens to every session and 1,113 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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