evo-macro-data-ingestion

evo-macro-data-ingestion is a skill for Claude Code, Codex from OpenLAIR/OpenSkill. It costs 47 tokens per session (611 once invoked), scanned A, original, Apache-2.0.

A Python utility for reading Economic Report of the President spreadsheet tables and Consumer Price Index files. It turns annual or quarterly spreadsheet data into clean yearly time series, including averages for incomplete years.

In plain words
What is it for?
Use it to load ERP economic tables and CPI data into pandas for later economic analysis.
Why use it?
It handles multi-row spreadsheet headings, different Excel formats, quarter labels, and the conversion of years into consistent integer indexes.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to load ERP economic tables and CPI data into pandas for later economic analysis.

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Install with agentmods
npx agentmods add skills/openlair/openskill/evo-macro-data-ingestion
Install

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.

Any agent
npx skills add OpenLAIR/OpenSkill --skill evo-macro-data-ingestion
Clone the repo
git clone --depth 1 https://github.com/OpenLAIR/OpenSkill

Made for: Claude Code, Codex.

Wrote 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.

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README.md
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Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 611 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00047 $0.00611
Opus 5 $0.00023 $0.00305
Sonnet 5 $0.00009 $0.00122
Haiku 4.5 $0.00005 $0.00061

Measured yesterday against content hash b17875b2623b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

evo-macro-data-ingestion 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 yesterday.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/data_ingestion.py, scripts/utils.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

tasks-evolved/econ-detrending-correlation/environment/skills/evo-macro-data-ingestion/SKILL.md · 57 lines

How it starts

The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.

evo-macro-data-ingestion

Parses Economic Report of the President (ERP) .xls tables and CPI .xlsx files into clean pandas Series indexed by integer year.

Key Functions

parse_erp_annual_total(filepath, target_year=2024)

Parses an ERP .xls file to extract the annual "Total" column (first data column).

  • Handles multi-row headers, trailing periods on years (e.g., '1973.')
  • Handles quarterly data at bottom of table
  • For partial years (e.g., 2024 with Q1-Q3 only), computes average of available quarters
  • Uses engine="xlrd" for .xls files
  • Returns: pd.Series indexed by integer year

compute_partial_year_average(df, target_year=2024)

Computes arithmetic mean of available quarterly SAAR values for a partial year.

  • Handles ERP quarterly format: '2024: I.' followed by indented ' II.', ' III p.'
  • Returns: float or None

process_cpi_annual(filepath)

Reads CPI data from .xlsx file. Auto-detects format:

  • Pre-processed annual data (Year + CPI columns)
  • Raw FRED monthly CPIAUCSL data (aggregated to annual mean)
  • Uses engine="openpyxl" for .xlsx files
  • Returns: pd.Series indexed by integer year

Usage

import sys
sys.path.insert(0, '/app/environment/skills/evo-macro-data-ingestion/scripts')
from utils import parse_erp_annual_total, process_cpi_annual

pce_nominal = parse_erp_annual_total('/root/ERP-2025-table10.xls', target_year=2024)
pfi_nominal = parse_erp_annual_total('/root/ERP-2025-table12.xls', target_year=2024)
cpi_annual = process_cpi_annual('/root/CPI.xlsx')

Data Format Notes

ERP Tables (.xls)

  • Rows 0-4: Multi-row headers (title, units, column labels)
  • Row 5+: Data rows with Period in col 0, Total in col 1
  • Years have trailing periods: '1973.'
  • Quarterly data appended at bottom: '2024: I.', ' II.', ' III p.'
  • Use xlrd engine (xlrd 2.0.1 only supports .xls)

CPI File (.xlsx)

  • May be annual (columns: Year, CPI_2024) or monthly FRED data
  • Use openpyxl engine for .xlsx files
  • CPI_2024 is normalized to 2024=1.0

Read the full file on GitHub · 57 lines

Files

What ships with it

2 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.

Changes

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.

  1. yesterday First seen · 57 lines · 47 tokens per session scan A b17875b2623b

Subscribe to this mod's changes

evo-macro-data-ingestion is a skill published in the GitHub repository OpenLAIR/OpenSkill (90 stars, last pushed yesterday), licensed Apache-2.0. It adds 47 tokens to every session and 611 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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