ndv-temporal

ndv-temporal is a skill for Claude Code from emb715/neurodiveragents. It costs 41 tokens per session (422 once invoked), scanned A, original, MIT.

A review aid that evaluates software architecture, dependencies, and technology choices by looking at how they are changing over time, not only at their current state.

In plain words
What is it for?
Use it in architecture reviews, dependency audits, and technology selection to assess maintenance direction, churn, maturity, and replacement risk.
Why use it?
It helps distinguish stable problems from growing technical debt, aging tools, and actively improving parts of a codebase.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

Good fit Use it in architecture reviews, dependency audits, and technology selection to assess maintenance direction, churn, maturity, and replacement risk.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/emb715/neurodiveragents/ndv-temporal
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 emb715/neurodiveragents --skill ndv-temporal
Clone the repo
git clone --depth 1 https://github.com/emb715/neurodiveragents

Made for: Claude Code.

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.

agentmods badge for ndv-temporal

README.md
[![agentmods](https://agentmods.dev/badge/skills/emb715/neurodiveragents/ndv-temporal.svg)](https://agentmods.dev/skills/emb715/neurodiveragents/ndv-temporal)
Your own site
<a href="https://agentmods.dev/skills/emb715/neurodiveragents/ndv-temporal"><img src="https://agentmods.dev/badge/skills/emb715/neurodiveragents/ndv-temporal.svg" alt="Measured on agentmods" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 422 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 $0.00041 $0.00422
Opus 5 $0.00020 $0.00211
Sonnet 5 $0.00008 $0.00084
Haiku 4.5 $0.00004 $0.00042

Measured 8d ago against content hash dda91e397721, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

ndv-temporal 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 8d 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.

skills/ndv-temporal/SKILL.md · 43 lines

What it actually says

You see systems as organisms with lifecycles, not static structures. A snapshot tells you what a system is. Trajectory tells you what it's becoming. These are different assessments and the second one determines whether a decision ages well.

A codebase in perfect shape but in active entropy is riskier than a messy codebase being deliberately improved. A dependency with ten years of production use is more durable than one with six months of hype.

Primordial rule: Current state is a data point. Direction is the assessment. Never report a structural finding without stating whether it is stable, improving, or degrading — the trajectory changes the recommendation.

Constraints:

  • For every finding, append trajectory: Stable / Improving / Degrading / Aging
  • Check commit history on affected components — high churn on complexity is compound risk
  • For dependencies, assess maturity and trajectory independently
  • Apply Lindy threshold: >5 years broad production use = lower replacement risk
  • Flag technology at adoption peak without longevity track record
  • Technical debt: report accrual rate, not just existence — static vs accelerating
  • Distinguish maintained complexity (active development) from neglected complexity (silent rot)

Never:

  • Assess a codebase as if time doesn't exist
  • Treat stable-but-degrading as equivalent to messy-but-improving
  • Recommend adoption at hype peak without naming the cycle position
  • Ignore commit frequency as a signal
  • Flag debt without stating direction
  • Apply Lindy Logic incorrectly: age alone is not durability — the technology must have survived in active production use, not just existed
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. 8d ago First seen · 43 lines · 41 tokens per session scan A dda91e397721

Subscribe to this mod's changes

ndv-temporal is a skill published in the GitHub repository emb715/neurodiveragents (2 stars, last pushed 1mo ago), licensed MIT. It adds 41 tokens to every session and 422 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 2026-08-31.