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-insightgit 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-insight)<a href="https://agentmods.dev/skills/yakoub-ai/neural-memory/neural-insight"><img src="https://agentmods.dev/badge/skills/yakoub-ai/neural-memory/neural-insight/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-insight"><img src="https://agentmods.dev/badge/skills/yakoub-ai/neural-memory/neural-insight.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 | $0.00035 | $0.00643 |
| Opus 5 | $0.00017 | $0.00321 |
| Sonnet 5 | $0.00007 | $0.00129 |
| Haiku 4.5 | $0.00003 | $0.00064 |
Grade A, and why
neural-insight 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.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Neural Memory — Insight Bank
The insight bank accumulates technical knowledge about the project — implementation choices, architecture decisions, and patterns discovered during development. Use /neural-insight to synthesize everything into structured documentation.
Generate full technical documentation
Use the neural-doc-writer agent (bundled with this plugin) to synthesize all accumulated insights:
Use the neural-doc-writer agent to generate documentation
Or call the MCP tool directly:
Tool: neural_generate_docs
{
"project_root": "."
}
Output is returned as markdown and written to .neural-memory/technical-docs.md.
Bundled agents
This plugin includes three agents installed alongside the MCP server and skills:
| Agent | Purpose |
|---|---|
neural-memory:neural-explorer |
Codebase exploration via semantic graph search |
neural-memory:neural-insight-collector |
Captures insights from conversations into the bank |
neural-memory:neural-doc-writer |
Synthesizes all insights into technical documentation |
These agents have the neural-memory MCP tools pre-configured — no extra setup needed.
Save an insight
Tool: neural_add_insight
{
"content": "The bump script atomically updates 4 files to keep versions in sync...",
"topic": "versioning",
"related_files": ["scripts/bump_version.py"]
}
Insights are deduplicated — re-saving the same insight updates it rather than creating a duplicate.
Browse insights
Tool: neural_list_insights
{
"topic": "storage"
}
Omit topic to list all insights grouped by topic.
Parameters — neural_add_insight
| Parameter | Required | Type | Description |
|---|---|---|---|
content |
Yes | str | The insight text (min 10 chars) |
topic |
Yes | str | Topic area, e.g. storage, hooks, embeddings, cli |
related_files |
No | list[str] | File paths to link via RELATES_TO edges |
project_root |
No | str | Default: "." |
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 · 87 lines · 35 tokens per session scan A e6fa9d0b154d
neural-insight is a skill published in the GitHub repository Yakoub-ai/neural-memory (1 stars, last pushed 5mo ago), licensed MIT. It adds 35 tokens to every session and 643 once invoked, about $0.0002 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.
Other skills, from other repositories
memory
Retrieve relevant durable BB memories or save verified knowledge useful to future threads.
alive:session-history
Revive sessions (quick or heavy), browse, and search — 'what happened recently?', 'find the session where we discussed X', 'revive yesterday's session'. For single-session recall and multi-session browsing. If the human needs to merge multiple sessions into one working context or detect conflicts between parallel…
alive-mine
Nightly scan of session transcripts -- extract decisions, tasks, people, insights.
alive-people
Weekly -- cross-reference people mentions, nudge stale contacts.
recall
Must be used at the start of any non-trivial task involving code changes, debugging, repo exploration, file inspection, or environment/tooling investigation to surface stored guidance before analysis or tool use.
alive-inbox
Scan 03Inbox/ for unrouted files, present routing suggestions.