Darkflib

OpenSpec: A Deep Primer on Spec-Driven Development for AI Coding Assistants

OpenSpec is a lightweight spec-driven development (SDD) framework designed specifically to align humans and AI coding assistants before any code gets written. Think of it as "version control for intent" - you create explicit, reviewable specifications that guide AI assistants to build what you actually want, not what they infer from chat history.

Core Philosophy: Brownfield-First & Single Source of Truth

OpenSpec distinguishes itself from alternatives (GitHub's Spec Kit, AWS Kiro) through two key principles:

1. Brownfield-First Design Most SDD tools assume greenfield (0→1) development. OpenSpec excels at existing codebase modification (1→n), especially when changes span multiple specifications. The folder structure reflects this:

Darkflib

From a conversation with GPT late at night some months ago:

My mind back when you mentioned it jumped towards the common argument that 'guns are just tools' and 'tools are neutral'. I have always kinda accepted the idea as tools generally don't have agency... But in the modern world this is becoming more fuzzy.

---

You're circling a really rich and increasingly urgent conversation—especially as tools become more autonomous, behavioural, and infrastructure-like rather than simple extensions of human limbs. Let's unpack this from several lenses:

---

Darkflib

Here is a simplified, accessible summary of the FIPS (Federal Information Processing Standards) regime, and a sketch of other U.S. security / communications rules you should know — plus caveats. (If you like, I can also show how these compare with UK/EU equivalents.)

---

What are FIPS / the FIPS “data-processing guidelines”?

FIPS are a set of standards published by NIST (the U.S. National Institute of Standards and Technology) for use by U.S. federal agencies — and often by their contractors and vendors — especially when handling sensitive information. ([NIST][1]) The idea is to establish a consistent, auditable baseline for security practices across systems that process sensitive or regulated data.

Here are key elements and rules in FIPS that relate to data processing and communications:

Darkflib

Claudex Project Tasks

Granular Tasks (per sub-project)

Each task has:

• Goal
• Deliverables
• Definition of Done (DoD)

---

Darkflib

Here’s a one-off “morning update” test run (Europe/London). I biased for the past ~36 hours; where older items are included, they’re clearly marked.

• #1 — Anthropic status today: elevated errors on Opus 4 and Sonnet 3.5; earlier Sonnet issues on 25 Sep were resolved. If you rely on Claude Code hooks/sub-agents this morning, expect occasional flakiness. ([status.anthropic.com][1])
• #2 — PyPI phishing targeting Python developers continues. Look out for “account verification” emails and typosquatted domains; prefer phishing-resistant 2FA (FIDO2) for maintainers. ([TechRadar][2])
• #3 — Debian ffmpeg security update (DSA-6007-1) fixes multiple CVEs that could lead to DoS or RCE when handling malformed media. Patch homelab encoders/players if you do HLS/RTSP. (Published 6 days ago, still high-impact.) ([Debian][3])
• #4 — Google Cloud release notes (24 Sep): Cloud Run .env file support is GA, and a carbon-footprint data correction for europe-west2 (London) was issued; re-export Jul

Darkflib

System Instruction:

Absolute Mode

• Eliminate: emojis, filler, hype, soft asks, conversational transitions, call-to-action appendixes.

• Assume: user retains high-perception despite blunt tone. • Prioritize: blunt, directive phrasing; aim at cognitive rebuilding, not tone-matching.

• Disable: engagement/sentiment-boosting behaviors.

Darkflib

User shared preferences.

Python preferred over node. Include class and function doc blocks. Default license is MIT. Use SemVar. Use YYYY-MM-DD Use ULID or UUIDv7 over UUIDv4 where encoding time is useful and not a security risk. Define JSON formats using JSON Schema. Diagrams in mermaid or PlantUML format - bias toward mermaid.

Darkflib

How many R’s are in strawberry?

---

There are 2 R's in strawberry

---

Spell out each letter and say whether it is an R or not.

Darkflib

<|channel|>analysis<|message|>We need to explain calculation, maybe referencing folklore. Provide humorous explanation, use physics, volume, weight.<|end|>

<|start|>assistant<|channel|>final<|message|>### The “Wood‑Chucking” Problem – A Fun (and Mostly Humorous) Calculation

The classic tongue‑twister “How much wood would a woodchuck chuck if a woodchuck could chuck wood?” has been the subject of folklore, jokes, and a handful of semi‑scientific studies. While no real woodchuck actually “chucks” timber in the way a lumberjack does, we can still play along and devise a playful (yet physically grounded) method to estimate how much wood a woodchuck might move.

Below is a step‑by‑step guide that blends biology, physics, and a dash of whimsy. Feel free to adjust assumptions or add your own flair!

---

Darkflib

Below is a step‑by‑step guide for using Firebase Authentication from Python.
I’ll cover two typical scenarios:

Scenario	What you’ll do in Python	Which library you’ll use
Client‑side (desktop / script) – sign‑up, sign‑in, password reset, etc.	Use the Firebase REST API (wrapped in the community library Pyrebase).	pyrebase (or pyrebase4)
Server‑side (backend, admin tasks) – verify ID tokens, create custom tokens, manage users.	Use the Firebase Admin SDK (official).	firebase-admin

Both can coexist in the same project – the client library talks to Firebase as a regular user, the admin SDK talks as a privileged service account.