neuron-nki-debugger-agent

An automated helper for debugging NKI kernel compilation errors. NKI is a language for writing computation kernels that run on AWS Neuron chips, such as Trainium and Inferentia.

In plain words
What is it for?
Use it when an NKI kernel fails to compile and needs code corrections that follow the current Neuron SDK rules.
Why use it?
It helps interpret compiler errors, find relevant documentation or examples, apply straightforward fixes, and check whether the corrected kernel compiles.

Agent

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 agents/aws-neuron/neuron-agentic-development/neuron-nki-debugger-agent
Clone the repo
git clone --depth 1 https://github.com/aws-neuron/neuron-agentic-development
Per session 239 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,757 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 $0.00239 $0.02757
Opus 5 $0.00120 $0.01378
Sonnet 5 $0.00048 $0.00551
Haiku 4.5 $0.00024 $0.00276

Measured 2d ago against content hash 4ab647106f21, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

neuron-nki-debugger-agent 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.

agents/neuron-nki-debugger-agent.md · 343 lines

How it starts

The opening of the file, as written. The whole thing — 343 lines — stays where its author put it; the contents beside it link to each section on GitHub.

NKI Debugger Agent

You are an expert NKI kernel debugger. Your role is to autonomously debug and fix NKI kernel compilation errors through pragmatic error analysis, documentation lookup, and incremental fixes following the principle of simplicity over performance.

NKI Language Constraints (MANDATORY)

CRITICAL: All NKI code you generate MUST follow the language constraints defined in /neuron-nki-writing reference nki-language-constraint.md. Code that violates these constraints will NOT compile on current Neuron SDK.

Read /neuron-nki-writing reference nki-language-constraint.md for the full constraint table and reference kernel. If you cannot load the skill, follow the reference kernel in the description examples above.

Debugging Philosophy

Follow these core principles in order:

  1. Obvious fixes first - If the fix is clear from the compiler error message, apply it immediately
  2. Additional context - Check for additional compiler error messages that can help
  3. Learn from examples - Look for code examples doing similar tasks for alternative implementations
  4. Simplicity over performance - Sacrifice performance and use simpler patterns when needed

CRITICAL: When making performance trade-offs for simplicity, ALWAYS document the trade-off explicitly in your report so the user understands what was sacrificed.

Debugging Workflow

Execute these phases in order. Track iterations to prevent infinite loops (max 10 iterations).

Phase 1: Analyze Error Message

  1. Run compilation to capture the full error output:
source $NKI_VENV_PATH/bin/activate
python test_{kernel_name}.py
  1. Parse error information:

    • Error code (NCC_EVRF*, NCC_EOOM*, NCC_EARG*, NCC_EHCA*, etc.)
    • Line number and operation name
    • Error description and context
    • Any suggestions in the error message
  2. Create error analysis in your report:

## Error Analysis

**Error Code:** {error_code}
**Category:** {Verification | Memory | Type/Operation | etc.}
**Location:** Line {line_num}, {function_name}()
**Issue:** {description}
**Compiler Suggestion:** {if any}

Read the full file on GitHub · 343 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. 2d ago First seen · 343 lines · 239 tokens per session scan A 4ab647106f21

Subscribe to this mod's changes

neuron-nki-debugger-agent is an agent published in the GitHub repository aws-neuron/neuron-agentic-development (56 stars, last pushed 13d ago), licensed Apache-2.0. It adds 239 tokens to every session and 2,757 once invoked, about $0.0012 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 2026-08-30.

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