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.
npx skills add Yakoub-ai/neural-memory --skill neural-statusgit clone --depth 1 https://github.com/Yakoub-ai/neural-memoryWrote 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.
[](https://agentmods.dev/skills/yakoub-ai/neural-memory/neural-status)<a href="https://agentmods.dev/skills/yakoub-ai/neural-memory/neural-status"><img src="https://agentmods.dev/badge/skills/yakoub-ai/neural-memory/neural-status/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yakoub-ai/neural-memory/neural-status"><img src="https://agentmods.dev/badge/skills/yakoub-ai/neural-memory/neural-status.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00026 | $0.00278 |
| Opus 5 | $0.00013 | $0.00139 |
| Sonnet 5 | $0.00005 | $0.00056 |
| Haiku 4.5 | $0.00003 | $0.00028 |
Grade A, and why
neural-status 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 10d 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.
What it actually says
Neural Memory — Status Check
Check the health and freshness of the neural memory index.
What this checks
- Whether neural memory has been initialized
- How many commits behind the index is
- Which files have changed since last index
- Total nodes, edges, and files in the graph
- Current index mode and configuration
How to call
Via MCP tool (neural-memory configured as MCP server in Claude Code):
Tool: neural_status
{}
Via Python (working directly in the project):
import asyncio
from neural_memory.server import neural_status, StatusInput
asyncio.run(neural_status(StatusInput()))
StatusInput has no required fields. Pass project_root="." to be explicit.
Windows: run
python -X utf8(or setPYTHONUTF8=1) to avoid cp1252 encoding errors from Unicode output. Applies to all neural commands.
Agent behavior
The neural agent runs this check automatically and will suggest:
/neural-indexif no index exists/neural-updateif the index is stale (default: 5+ commits behind)
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.
- 10d ago First seen · 41 lines · 26 tokens per session scan A 1db51be9ffac
neural-status is a skill published in the GitHub repository Yakoub-ai/neural-memory (1 stars, last pushed 5mo ago), licensed MIT. It adds 26 tokens to every session and 278 once invoked, about $0.0001 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.
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