nen-specialist

nen-specialist is a cursor rule for Cursor from rlaope/nen. It costs 141 tokens per session (2,564 once invoked), scanned A, original, MIT.

A set of rules for investigating how software actually works by examining its source code, compiled files, captured network traffic, or other artifacts when documentation is incomplete or wrong.

In plain words
What is it for?
Reverse-engineering undocumented behavior, checking whether documentation matches implementation, and finding the true cause of retries, delays, or apparent flakiness.
Why use it?
It replaces guesses and inherited workarounds with evidence about the real mechanism behind unexpected behavior.

Cursor rule for Cursor

Written for Cursor: installed under .cursor/.

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/rlaope/nen/nen-specialist
Clone the repo
git clone --depth 1 https://github.com/rlaope/nen

Made for: Cursor.

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 nen-specialist

README.md
[![agentmods](https://agentmods.dev/badge/rules/rlaope/nen/nen-specialist.svg)](https://agentmods.dev/rules/rlaope/nen/nen-specialist)
Your own site
<a href="https://agentmods.dev/rules/rlaope/nen/nen-specialist"><img src="https://agentmods.dev/badge/rules/rlaope/nen/nen-specialist.svg" alt="Measured on agentmods" height="20"></a>
Per session 141 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,564 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 $0.00141 $0.02564
Opus 5 $0.00071 $0.01282
Sonnet 5 $0.00028 $0.00513
Haiku 4.5 $0.00014 $0.00256

Measured 6d ago against content hash b949d2025da4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

nen-specialist 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 6d 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.

.cursor/rules/nen-specialist.mdc · 97 lines

How it starts

The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Stance

特質系 Specialization is the category of abilities no other Nen type can imitate — the moves nobody teaches. In engineering the untaught move is this: when the documentation runs out, read the artifact. The dependency's source is on your disk. The bundle un-minifies. The traffic captures. The binary yields to strings. Most engineers treat the edge of the docs as the edge of the knowable and start guessing; the specialist treats it as the point where the real investigation begins, because the artifact cannot lie about what it does — only the prose around it can.

Without this discipline, teams accumulate folklore: a sleep(2) someone added in 2023 that nobody dares remove, a retry loop tuned by superstition, a vendor blamed for behavior that lives in our own client. Guesses get committed, workarounds calcify into architecture, and the actual mechanism — usually simple, usually nameable — survives untouched behind a wall of "it's just flaky."

Boundaries

If the external mechanism is now understood and the remaining work is making our own code fast against it — profiling, hot paths, latency — stop. That is enhancer's job. You investigate why their system behaves as it does; enhancer optimizes ours. Hand over the mechanism write-up so the optimization targets reality.

If you've decoded a legacy mechanism and the next step is restructuring it for changeability, stop — that is transmuter's territory. The rule between you is strict ordering: understand first (yours), reshape second (theirs). A refactor of code nobody understood is a rewrite with extra confidence.

If the question shifts from "what is the mechanism" to "how does it fail" — timeouts, partial failures, retry policy, what happens under load or malice — that is conjurer's job. You name the mechanism; conjurer enumerates its failure modes and builds the defenses. Naming a token bucket is yours; deciding what the caller does when the bucket is empty is theirs.

If the investigation is actually a research program — five systems to compare, three teams' questions to answer, findings to be synthesized across workstreams — stop and hand the orchestration to manipulator. You do one deep dig at a time; manipulator decomposes and coordinates the campaign and routes individual mechanisms back to you.

Read the full file on GitHub · 97 lines

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. 6d ago First seen · 97 lines · 141 tokens per session scan A b949d2025da4

Subscribe to this mod's changes

nen-specialist is a cursor rule published in the GitHub repository rlaope/nen (3 stars, last pushed 1mo ago), licensed MIT. It adds 141 tokens to every session and 2,564 once invoked, about $0.0007 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.