industrial-ai-troubleshooting-agent: Instructions file for Claude Code

CLAUDE.md

industrial-ai-troubleshooting-agent CLAUDE.md is an instructions file for Claude Code from ScottDuncanAI/industrial-ai-troubleshooting-agent. It costs 6,180 tokens per session, scanned A, original, Apache-2.0.

System instructions for an AI assistant connected to four data sources about a coal-fired boiler: sensor history, alarm records, an equipment-relationship graph, and plant documents. The rules define how to query these sources and cite procedures or limits.

In plain words
What is it for?
They help answer questions about sensor readings, alarms, equipment relationships, operating procedures, and plant documentation using the available records.
Why use it?
They prevent incorrect time ranges, unsupported answers, and uncited safety-related claims. They also require document access through the server’s search and retrieval tools.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: mentions Claude Code.

This is ScottDuncanAI/industrial-ai-troubleshooting-agent's own configuration. It tells Claude Code how to work on industrial-ai-troubleshooting-agent itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything industrial-ai-troubleshooting-agent configures →

Reuse

Borrowing it

Nothing to install: this file belongs to ScottDuncanAI/industrial-ai-troubleshooting-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/ScottDuncanAI/industrial-ai-troubleshooting-agent/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/ScottDuncanAI/industrial-ai-troubleshooting-agent

Made for: Claude Code.

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Per session 6,180 This file is loaded in full into every session.
When invoked 6,180 The same file — it is already loaded in full.
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.06180 $0.06180
Opus 5.5 $0.02472 $0.02472
Sonnet 5.5 $0.01236 $0.01236
Haiku 4.5 $0.00618 $0.00618

Measured 2mo ago against content hash 0b461397f278, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

industrial-ai-troubleshooting-agent CLAUDE.md 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 2mo 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.md · 435 lines

How it starts

The opening of the file, as written. The whole thing — 435 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Boiler Historian — System Reference

This system connects an LLM to four data sources for a coal-fired CFB boiler at a chemical plant in Zhejiang, China: a time-series historian (5 days of sensor data), a DCS alarm log (6,005 alarm events derived from the historian), a process knowledge graph (equipment topology and relationships), and a plant document library (62 procedures, datasheets, and guides). Together they enable natural-language operations queries grounded in real data and real documentation.


Critical Rules — Read First

These apply to every response, no exceptions:

  1. Never read files directly. Do not use Read, Grep, or Glob on the RAG docs/ folder or any project file. All document access must go through the MCP tools (docs_search, docs_list_documents, docs_get_document).

  2. Always resolve relative time before any historian query. If the user says "past 3 hours", "last day", or "this morning", call historian_get_data_range first to get the latest timestamp, then compute the absolute start time. Never guess a time window.

  3. Always cite sources when quoting procedures or limits. Format: "Per [Document Title], Rev [X.X]: ..." — include document title and revision for every piece of procedural or specification information you present.

  4. Do not invent tag names. Only use tags confirmed by historian_list_tags or historian_search_tags. If a tag name is uncertain, search first.

  5. Flag anomalies proactively. Whenever TE_8332A is in scope and its value is outside 530–545°C, call it out explicitly as outside the normal operating range, even if the user didn't ask about it directly.


The Four Data Sources

1. Historian (DuckDB)

  • File: boiler_historian.duckdb
  • Data: 86,400 rows × 30 tags at 5-second intervals
  • Time range: 2022-03-27 14:28:54 → 2022-04-01 14:28:49 (5 days)
  • This is a static snapshot. There is no live feed. "Now" = the latest timestamp.

Read the full file on GitHub · 435 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. 2mo ago First seen · 435 lines · 6,180 tokens per session scan A 0b461397f278

Subscribe to this mod's changes

industrial-ai-troubleshooting-agent CLAUDE.md is an instructions file published in the GitHub repository ScottDuncanAI/industrial-ai-troubleshooting-agent (106 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 6,180 tokens to every session, about $0.0247 per session on Opus 5.5. 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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