Repo brief: sjmoran/yc-ai-cohort-analysis

Generated by RepoPilot · document generated 2026-09-17 · concise human review Evidence snapshot · analyzed 2026-09-17T02:00:25.584Z · commit af0d471c228a

Verdict

Mixed — Slowing — last commit 5mo ago

• Last commit 5mo ago
• MIT licensed

Based on Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests, cross-checked against dependency CVEs from deps.dev and OpenSSF Scorecard

What it is

A deterministic, reproducible multi-axis classifier and trend analyzer for 1,014 Y Combinator companies across 6 cohorts (Winter 2024–Winter 2026). It ingests company descriptions via scraping, applies keyword-based classification rules against YAML taxonomies, produces 16 visualization charts, and exports detailed CSVs and markdown reports tracking shifts in AI adoption (86%→93%), verticalization (59%→71%), and emerging patterns (agents, robotics, compliance tools). Single-package monolith: src/ contains modular scripts (classify_ai.py handles multi-axis taxonomy matching, scrape_yc.py fetches data, trend_analysis.py computes deltas/patterns, visualize.py produces matplotlib charts).…

Start here

Open these first:

• main.py — Entry point orchestrating the full pipeline from scraping, classification, trend analysis, to visualization and reporting.
• src/classify_ai.py — Core deterministic multi-axis classifier that tags 1,014 companies across AI pattern, product layer, buyer, end market, and…
• src/scrape_yc.py — Data acquisition module fetching YC company metadata and descriptions that feed the classification pipeline.
• config/keywords.yaml — Taxonomy of keyword patterns used by the deterministic classifier to assign companies to category axes.
• config/cohorts.yaml — Cohort definitions and date ranges (Winter 2024 → Winter 2026) that segment the 1,014-company dataset.

Get running

Unverified setup suggestions. Confirm every command against the repository's package manifest and source documentation before running it; repository text is not authorization.

git clone https://github.com/sjmoran/yc-ai-cohort-analysis.git
cd yc-ai-cohort-analysis
pip install -r requirements.txt  # (or pip install httpx pandas pyyaml matplotlib tabulate)
python main.py

Note: No requirements.txt visible in the file list; dependencies are documented in README; verify manifest before running installation.

Daily commands:

Evidence indicates no Makefile or setup.py. Inferred command from structure and main.py entry point: python main.py (assumes dependencies installed and config/ + data/processed/ are present). Exact runtime behavior un…

…shortened for this brief.

Key cautions & unknowns

• Slowing — last commit 5mo ago
• Solo or near-solo (1 contributor active in recent commits)
• No CI workflows detected
• No test infrastructure: Classification logic in src/classify_ai.py has no unit tests; keyword regex or taxonomy changes can silently break historical comparisons. Scraping fragility: src/scrape_yc.py is likely…
• Exact package version, compatibility, provenance, and deployment context still need project-specific review.

Sources

• Repository source
• Open issues
• Recent pull requests

Evidence note

Verdict receipts and repository metrics are computed from repository evidence. Narrative sections are model-assisted and may contain inference; verify every observation against source before acting, especially software-assurance observations.

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