neuron-nki-profile-querying

neuron-nki-profile-querying is a skill for Claude Code from aws-neuron/neuron-agentic-development. It costs 207 tokens per session (4,370 once invoked), scanned A, original, Apache-2.0.

A workflow for querying and analyzing NKI kernel performance profiles from Neuron Explorer files. NKI is the Neuron Kernel Interface, and kernel profiles record how code runs on AWS Trainium hardware.

In plain words
What is it for?
Use it to ingest NEFF compiled kernels and NTFF traces, query profile tables through a local API, and calculate performance limits or inefficiencies from parquet files.
Why use it?
It lets developers inspect recorded performance data locally with SQL or Python instead of manually reading raw traces.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Good fit Use it to ingest NEFF compiled kernels and NTFF traces, query profile…

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Install with agentmods
npx agentmods add skills/aws-neuron/neuron-agentic-development/neuron-nki-profile-querying
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 aws-neuron/neuron-agentic-development --skill neuron-nki-profile-querying
Clone the repo
git clone --depth 1 https://github.com/aws-neuron/neuron-agentic-development

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 neuron-nki-profile-querying

README.md
[![agentmods](https://agentmods.dev/badge/skills/aws-neuron/neuron-agentic-development/neuron-nki-profile-querying.svg)](https://agentmods.dev/skills/aws-neuron/neuron-agentic-development/neuron-nki-profile-querying)
Your own site
<a href="https://agentmods.dev/skills/aws-neuron/neuron-agentic-development/neuron-nki-profile-querying"><img src="https://agentmods.dev/badge/skills/aws-neuron/neuron-agentic-development/neuron-nki-profile-querying.svg" alt="Measured on agentmods" height="20"></a>
Per session 207 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,370 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00207 $0.04370
Opus 5 $0.00103 $0.02185
Sonnet 5 $0.00041 $0.00874
Haiku 4.5 $0.00021 $0.00437

Measured 7d ago against content hash 46eeb97faff6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

neuron-nki-profile-querying scanned grade A with 1 finding 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 7d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

on localhost. No deployment, no remote service — just the CLI and curl.
skills/neuron-nki-profile-querying/SKILL.md · 438 lines

How it starts

The opening of the file, as written. The whole thing — 438 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Profile Querying

Run SQL queries against NKI kernel profile data using neuron-explorer view. This ingests NEFF+NTFF into parquet and exposes a DuckDB-backed API server on localhost. No deployment, no remote service — just the CLI and curl.

For more advanced analysis, use python on parquet to compute performance bounds and investigate precise inefficiencies within arbitrary execution intervals.

What you need: A compiled NEFF file and a captured NTFF trace file. These come from /neuron-nki-profiling or from running a kernel with the right env vars and neuron-explorer capture.

Quick Start

# Ingest and start API server (no web UI)
neuron-explorer view \
  -n ./kernel.neff \
  -s ./profile.ntff \
  --data-path ~/.local/share/neuron-profile \
  --display-name my-kernel \
  --disable-ui &

# Wait for server
sleep 10

# Query
curl -s -X POST http://localhost:3002/api/v1/db/my-kernel/_search \
  -H 'Content-Type: application/json' \
  -d '{"type":"databaseExplorerQuery","tableName":"Summary","query":"SELECT total_time, mfu_estimated_percent, tensor_engine_active_time_percent, dma_active_time_percent FROM Summary"}'

That's it. Ingest, serve, query.

Prerequisites

  • neuron-explorer installed (comes with AL2023 DLAMI or aws-neuronx-tools)
  • NEFF file (compiled kernel binary) + NTFF file (execution trace)

Check availability:

which neuron-explorer && neuron-explorer --version

If not found, check /opt/aws/neuron/bin/neuron-explorer.


Step-by-Step Workflow

Step 0: Check Profile Quality (Re-profile if Needed)

Note: This step is specific to NKI kernel development. If you are querying a profile that was generated outside of an NKI workflow, skip to Step 1.

Disclaimer: Query results are only as good as the profile. If the NEFF/NTFF were captured without the right env vars, key tables (DmaPacket, DmaPacketAggregated) may be empty and source-level attribution will be missing.

Check whether the profile has the data you need:

# After ingesting (Step 2), check for DMA packet data
curl -s -X POST http://localhost:3002/api/v1/db/${PROFILE_NAME}/_search \
  -H 'Content-Type: application/json' \
  -d '{"type":"databaseExplorerQuery","tableName":"DmaPacket","query":"SELECT COUNT(*) as cnt FROM DmaPacket"}'

Read the full file on GitHub · 438 lines

Files

What ships with it

34 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 7d ago First seen · 438 lines · 207 tokens per session scan A 46eeb97faff6

Subscribe to this mod's changes

neuron-nki-profile-querying is a skill published in the GitHub repository aws-neuron/neuron-agentic-development (57 stars, last pushed 18d ago), licensed Apache-2.0. It adds 207 tokens to every session and 4,370 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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