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 agentmods add skills/pdudotdev/ainoc/redistributionnpx skills add pdudotdev/aiNOC --skill redistributiongit clone --depth 1 https://github.com/pdudotdev/aiNOCWhat 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 | $0.00032 | $0.01722 |
| Opus 5 | $0.00016 | $0.00861 |
| Sonnet 5 | $0.00006 | $0.00344 |
| Haiku 4.5 | $0.00003 | $0.00172 |
Grade A, and why
Redistribution Troubleshooting 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 3d 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.
The source is not reproduced here
Licensed GPL-3.0
The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- 3d ago First seen · 114 lines · 32 tokens per session scan A 20b8208832ef
Redistribution Troubleshooting is a skill published in the GitHub repository pdudotdev/aiNOC (11 stars, last pushed 3d ago), licensed GPL-3.0. It adds 32 tokens to every session and 1,722 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 2026-08-30.
Other skills, from other repositories
arxiv-mcp-server
Use when finding, comparing, reading, or monitoring arXiv papers, including requests for abstracts, citation graphs, original LaTeX, section-level technical details, or literature reviews.
excel-cli
Excel CLI automation skill for Windows workbooks. Use when a coding agent needs token-efficient, scriptable, or unattended Excel automation via excelcli commands. Best for CI/CD, scheduled jobs, batch processing, PowerShell workflows, and bulk workbook edits. Supports Power Query, DAX, PivotTables, Tables, Ranges…
excel-mcp
Excel MCP Server skill for Windows workbook automation. Use when an assistant needs rich MCP tools to create, inspect, modify, format, or analyze Excel files. Supports Power Query (M), Data Model/DAX, PivotTables, Tables, Ranges, Charts, Slicers, formatting, screenshots, VBA macros, connections, and calculation mode.…
powerpoint-cli
PowerPoint CLI automation skill for Windows presentations. Use when a coding agent needs token-efficient, scriptable, or unattended PowerPoint automation via pptcli commands. Best for CI/CD, scheduled jobs, batch processing, PowerShell workflows, and bulk deck edits. Supports slides, shapes, text frames, tables…
powerpoint-mcp
PowerPoint MCP Server skill for Windows presentation automation via a live PowerPoint desktop instance (COM/PIA). Use when an assistant needs rich MCP tools to create, open, build, format, and export PowerPoint (.pptx/.pptm) presentations — slides, shapes, text boxes, tables, native charts, images, audio, video…
agent-ops
This skill should be used when the user asks about agent architecture, evaluation, metrics, production monitoring, debugging agents, or best practices for building reliable AI agents. Use for questions like "evaluate my agent", "set up production monitoring", "add guardrails", "detect hallucinations", "agent…