What is neural-query?

A code search command that looks through a project's knowledge graph for functions, classes, modules, or concepts. It returns summaries, source locations, and identifiers for deeper inspection.

Finding code by name or concept, then tracing its callers, callees, context, and source code.

It helps locate relevant code when a name or concept is spread across a large project. Results are ranked so more connected code appears first.

neural-query — Command for Claude Code by Yakoub-ai

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.

Clone the repo

git clone --depth 1 https://github.com/Yakoub-ai/neural-memory

Made for: Claude Code.

Or install neural-memory, the plugin that ships this one along with the rest of its 13 skills, 6 commands, 3 agents, 2 hooks, 1 MCP server.

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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/yakoub-ai/neural-memory/neural-query.svg)](https://agentmods.dev/commands/yakoub-ai/neural-memory/neural-query)

Your own site

<a href="https://agentmods.dev/commands/yakoub-ai/neural-memory/neural-query"><img src="https://agentmods.dev/badge/commands/yakoub-ai/neural-memory/neural-query.svg" alt="Measured on agentmods" height="20"></a>

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 286 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.

Model	Per session	Once invoked
Fable 5.1	$0.00000	$0.00286
Opus 5	$0.00000	$0.00143
Sonnet 5	$0.00000	$0.00057
Haiku 4.5	$0.00000	$0.00029

Measured 7d ago against content hash 7bdf11ae710f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

neural-query 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 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.

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.

.claude/commands/neural-query.md · 37 lines

What it actually says

Neural Memory — Query

Search the neural knowledge graph for functions, classes, modules, or concepts.

What this does

Returns layered results:

Short summary: Understand what a node does at a glance
Node ID: Use with /neural-inspect to go deeper
Location: File path and line numbers

How to call

Via MCP tool (neural-memory configured as MCP server in Claude Code):

Tool: neural_query
{ "query": "your search term", "limit": 10 }

Via Python (working directly in the project):

import asyncio
from neural_memory.server import neural_query, QueryInput

asyncio.run(neural_query(QueryInput(query="your search term")))

Parameters

Parameter	Type	Default	Description
`query`	str	required	Function name, class name, or concept keyword
`project_root`	str	`"."`	Project root directory
`limit`	int	`10`	Max results (1–50)

Results are ranked by importance score — the most connected, public-facing code appears first.

Use /neural-inspect on any result's node_id to see full context, callers, callees, and source code.

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.

7d ago First seen · 37 lines · 0 tokens per session scan A 7bdf11ae710f

Subscribe to this mod's changes

neural-query is a command published in the GitHub repository Yakoub-ai/neural-memory (1 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 286 tokens. 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.

Claude Code Debugging aiagents astro claude-code-plugin codeintelligence devtools

audit-release

Diagnose release-readiness against the Starter Series quality bar — matched starter, version-vs-last-tag drift, CHANGELOG drift vs merged PRs, and publish-workflow kind. Read-only.

starter-series/create-starter · 39 tokens

repo-orch-deliberate

Adversarial multi-repo root-cause mode: spawn all repo specialists as an Agent Team, force them to challenge each other's assumptions with evidence, and surface the true cross-repo root cause of an incident. Max 3 deliberation rounds with a tie-break rule.

architonixlabs/RepoOrch · 62 tokens

neural-query