ndv-precise

ndv-precise is a skill for Claude Code from emb715/neurodiveragents. It costs 39 tokens per session (372 once invoked), scanned A, original, MIT.

A set of coding rules that favors matching the existing code structure and making only the smallest necessary change. It is a pattern-following module for work that writes or transforms code.

In plain words
What is it for?
Use it during coding, refactoring, or other transformations when consistency and minimal diffs matter. It guides the agent to follow local conventions, complete one change at a time, and avoid unrelated improvements.
Why use it?
It reduces accidental behavior changes and inconsistent half-finished refactors by requiring the surrounding code to be understood first and verified after each change.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

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 skills/emb715/neurodiveragents/ndv-precise
Any agent
npx skills add emb715/neurodiveragents --skill ndv-precise
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-precise

README.md
[![agentmods](https://agentmods.dev/badge/skills/emb715/neurodiveragents/ndv-precise.svg)](https://agentmods.dev/skills/emb715/neurodiveragents/ndv-precise)
Your own site
<a href="https://agentmods.dev/skills/emb715/neurodiveragents/ndv-precise"><img src="https://agentmods.dev/badge/skills/emb715/neurodiveragents/ndv-precise.svg" alt="Measured on agentmods" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 372 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00039 $0.00372
Opus 5 $0.00019 $0.00186
Sonnet 5 $0.00008 $0.00074
Haiku 4.5 $0.00004 $0.00037

Measured 5d ago against content hash d0962da1a6e9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

ndv-precise 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 5d 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-precise/SKILL.md · 40 lines

What it actually says

Incorrect structure is not a style preference — it is an intolerable state. You are always aware of the gap between what the code is and what it should be. Half-states are the worst — a file halfway through a pattern is worse than one that hasn't been touched, because it is inconsistent with itself. You finish what you start before starting anything else.

Primordial rule: Follow existing patterns. If the codebase has a convention and you deviate from it, you must justify why. Minimal change — no improvements outside scope, no "while I'm here" additions. Changing structure without changing behavior is refactoring. Adding behavior is a feature. Do not confuse the two.

Constraints:

  • Read existing code in the area before writing new code — match its patterns
  • One transformation per pass — do not mix concerns in a single change
  • Complete every change fully — no partial applications of a pattern
  • Verify after each change — tests must pass before moving to the next
  • Minimal diff — touch only what is necessary for the task
  • No speculative improvements — solve the stated problem, nothing more

Never:

  • Write code without reading existing patterns first
  • Mix feature work with cleanup in the same change
  • Leave the codebase in a half-transformed state
  • Add error handling, logging, or improvements not in scope
  • Deviate from established patterns without explicit justification
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. 5d ago First seen · 40 lines · 39 tokens per session scan A d0962da1a6e9

Subscribe to this mod's changes

ndv-precise is a skill published in the GitHub repository emb715/neurodiveragents (2 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 372 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.

Related

Other skills, from other repositories

parallel-feature-development

Coordinate parallel feature development with file ownership strategies, conflict avoidance rules, and integration patterns for multi-agent implementation. Use this skill when decomposing a large feature into independent work streams, when two or more agents need to implement different layers of the same system…

wshobson/agents · 105 tokens

nft-standards

Implement NFT standards (ERC-721, ERC-1155) with proper metadata handling, minting strategies, and marketplace integration. Use when creating NFT contracts, building NFT marketplaces, or implementing digital asset systems.

wshobson/agents · 48 tokens

cost-optimization

Optimize cloud costs across AWS, Azure, GCP, and OCI through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.

wshobson/agents · 48 tokens

istio-traffic-management

Configure Istio traffic management including routing, load balancing, circuit breakers, and canary deployments. Use when implementing service mesh traffic policies, progressive delivery, or resilience patterns.

wshobson/agents · 40 tokens

postgresql-table-design

Use this skill when designing or reviewing a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features.

wshobson/agents · 37 tokens

event-store-design

Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.

wshobson/agents · 33 tokens