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 OpenLAIR/OpenSkill --skill evo-excel-data-extractiongit clone --depth 1 https://github.com/OpenLAIR/OpenSkillWrote 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/openlair/openskill/evo-excel-data-extraction)<a href="https://agentmods.dev/skills/openlair/openskill/evo-excel-data-extraction"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-excel-data-extraction/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/openlair/openskill/evo-excel-data-extraction"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-excel-data-extraction.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 | $0.00046 | $0.00494 |
| Opus 5 | $0.00023 | $0.00247 |
| Sonnet 5 | $0.00009 | $0.00099 |
| Haiku 4.5 | $0.00005 | $0.00049 |
Grade A, and why
evo-excel-data-extraction scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
evo-excel-data-extraction
Utilities for reading IMF commodity price data and template workbook structures.
Key Functions
extract_gold_price_series(filepath)- Extract gold price (US$/troy oz) time series from IMF file. Returns list of (date_str, price) tuples.extract_country_reserve_data(filepath, sheet_name, year_row=18)- Extract country gold reserves from Value/Volume sheets. Returns dict with country data.extract_total_reserves_data(filepath, year_row=18)- Extract total reserves for 2025.explore_sheet_structure(filepath)- Get sheet dimensions and info.extract_country_names_from_desc(desc_str)- Parse country name from column description.
Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-excel-data-extraction/scripts')
from utils import extract_gold_price_series, extract_country_reserve_data, extract_total_reserves_data
gold_series = extract_gold_price_series('/root/data/imf-commodity-prices.xlsx')
value_countries = extract_country_reserve_data('/root/data/test-rar.xlsx', 'Value')
volume_countries = extract_country_reserve_data('/root/data/test-rar.xlsx', 'Volume')
total_reserves = extract_total_reserves_data('/root/data/test-rar.xlsx')
Data Layout Notes
- IMF file: Single sheet, PGOLD column (BY/col 77), data rows 5-433, dates like "1990M1" to "2025M9"
- Template Gold price sheet: rows 2-430, dates in col A, prices go in col B
- Value sheet: row 18 = 2025 data, columns C-R have different countries
- Volume sheet: row 18 = 2025 data, volumes in various units (Mil.Troy Ounce, Thous.Troy Ounce)
- Total Reserves sheet: row 18 = 2025 data
- Answer sheet: Step 1 (rows 3-6), Step 2 (rows 11-13), Step 3 (rows 20-24)
What ships with it
1 file 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.
- today First seen · 39 lines · 46 tokens per session scan A ef9bb6cbfc75
evo-excel-data-extraction is a skill published in the GitHub repository OpenLAIR/OpenSkill (88 stars, last pushed yesterday), licensed Apache-2.0. It adds 46 tokens to every session and 494 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 2026-09-11.
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