blindspot

Knowledge resilience report

Repository: /private/tmp/cohort10/agent-rules
Generated 2026-05-20 13:05 UTC · window: last 90 days · blindspot v0.2.0

Executive brief

Fragile Resilience 40/100 · F · doc only profile

Business implication Code surface is too small for confident structural claims; treat any concentration signal as informational only.

Executive summary

Establish a successor for Peter Steinberger (steipete@gmail.com)'s work — 1 files would orphan without them

Resilience is **Fragile** (40/100). Weakest dimension: ownership concentration (F). Repo profile: doc-only — very little code surface for this analysis. Treat results with caution.

Risk inventory: 1 file(s) would become orphans if the top contributor leaves.

Top recommended action: Establish a successor for Peter Steinberger (steipete@gmail.com)'s work — 1 files would orphan without them

💡 Want a richer, prose-style executive summary? Add a cloud LLM key (Anthropic or OpenAI) to your scan:
--api-key sk-ant-... --provider anthropic --model claude-sonnet-4-6
or set narrative.api_key in .blindspot.yaml. Without a key, this rule-based narrator is used — deterministic, in-process, no network.

Overview

Engineering Resilience Score

Overall
40/100 F
Fragile

Fragile resilience overall (score 40). Weakest dimension: ownership concentration at 0.

Doc-only Very little code surface — treat results with caution.

Key signals — the six questions

Six concrete questions, each with a one-number answer. This is the report. Everything below is supporting detail; run with --detailed for the deep-dive sections.

Ownership concentration
No service rests on a single owner
Every service has at least two people who know it.
Single-engineer dependency
1 files orphan if the top contributor leaves
These files would have no confident owner the day that person walks out.
Knowledge decay
No file is critically decayed
Owners are still close to the code they own.
Review depth
No review data (local git only)
Connect a GitHub/Bitbucket remote to measure review depth.
Correction load
Features land without a bugfix tail
Code ships and stays shipped — low rework pressure.
AI-readable context
Repo lacks AI-readable operational context (0/5)
No agent rules (CLAUDE.md), specs, architecture notes / ADRs at the repo root — a new human or AI agent must reverse-engineer the codebase.