spec-generation

Guidelines for producing technical specification documents: written plans that describe what should be built and how it should behave.

In plain words
What is it for?
Use them when writing specifications for complex changes that need to be clear to experienced developers and consistent with the existing codebase.
Why use it?
They encourage clear requirements, appropriate tests, and reuse of established project patterns instead of unnecessary custom designs.

Cursor rule

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.

agentmods
npx agentmods add rules/nlewis84/ai-rules/spec-generation
Clone the repo
git clone --depth 1 https://github.com/nlewis84/ai-rules
Per session 27 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,258 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00027 $0.02258
Opus 5 $0.00014 $0.01129
Sonnet 5 $0.00005 $0.00452
Haiku 4.5 $0.00003 $0.00226

Measured 2d ago against content hash e5dd8c4730c0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

spec-generation 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 2d ago.

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.

spec-generation.mdc · 359 lines

The source is not reproduced here

Licensed GPL-3.0

The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

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. 2d ago First seen · 359 lines · 27 tokens per session scan A e5dd8c4730c0

Subscribe to this mod's changes

spec-generation is a cursor rule published in the GitHub repository nlewis84/ai-rules (3 stars, last pushed 10mo ago), licensed GPL-3.0. It adds 27 tokens to every session and 2,258 once invoked, about $0.0001 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 2026-08-31.