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 xuansenpa1/skillrevise --skill data-reconciliationgit clone --depth 1 https://github.com/xuansenpa1/skillreviseWrote 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/xuansenpa1/skillrevise/data-reconciliation)<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/data-reconciliation"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/data-reconciliation/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/xuansenpa1/skillrevise/data-reconciliation"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/data-reconciliation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.00679 |
| Opus 5 | $0.00000 | $0.00340 |
| Sonnet 5 | $0.00000 | $0.00136 |
| Haiku 4.5 | $0.00000 | $0.00068 |
Grade A, and why
data-reconciliation 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Reconciliation for Spreadsheets
Techniques for recovering missing values from financial and tabular data using mathematical constraints.
Core Principles
1. Row/Column Sum Constraints
When totals are provided, missing values can be recovered:
Missing = Total - Sum(Known Values)
Example: If a row sums to 1000 and you know 3 of 4 values (200, 300, 400), the missing value is:
Missing = 1000 - (200 + 300 + 400) = 100
2. Year-over-Year (YoY) Change Recovery
When you have percentage changes between periods:
Current = Previous × (1 + YoY_Change/100)
To recover a previous value from current:
Previous = Current / (1 + YoY_Change/100)
3. Percentage Share Recovery
When you know a value's share of the total:
Value = Total × (Share/100)
Example: If total budget is 50000 and a department's share is 20%:
Value = 50000 × 0.20 = 10000
4. Compound Annual Growth Rate (CAGR)
For multi-year growth analysis:
CAGR = ((End_Value / Start_Value)^(1/years) - 1) × 100
Example: If Year 1 was 1000 and Year 5 is 1500 (4 years of growth):
CAGR = ((1500/1000)^(1/4) - 1) × 100 = 10.67%
To recover a start or end value:
End = Start × (1 + CAGR/100)^years
Start = End / (1 + CAGR/100)^years
5. Cross-Validation
Always verify recovered values:
- Do row totals match column totals?
- Are percentage shares consistent?
- Do YoY changes recalculate correctly?
Recovery Strategy
- Identify constraints: What mathematical relationships exist?
- Find solvable cells: Which missing values have enough information?
- Solve in order: Some values may depend on others (chain dependencies)
- Validate: Check all constraints still hold
Chain Dependencies
Sometimes you must solve values in a specific order:
- Recover budget value A from Sheet 1
- Use A to calculate YoY percentage in Sheet 2
- Use that percentage to verify or calculate another value
Always map out dependencies before starting.
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 · 92 lines · 0 tokens per session scan A 59f07a0eafef
data-reconciliation is a skill published in the GitHub repository xuansenpa1/skillrevise (56 stars, last pushed 7d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 679 tokens. 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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