bi-mcp: Skill for Claude Code

.claude/skills/bi-troubleshoot/SKILL.md

bi-troubleshoot is a skill for Claude Code from whoamiTM/bi-mcp. It costs 53 tokens per session (943 once invoked), scanned A, original, MIT.

A guided troubleshooting procedure for alert problems on a specific Blue Iris security camera. Blue Iris is software that records camera video and detects events.

In plain words
What is it for?
Investigating why a camera misses alerts, sends false alerts, labels activity incorrectly, or alerts at the wrong times.
Why use it?
It helps separate missing, incorrect, or badly timed alerts from other camera problems. It checks the recorded alert data and settings before testing one likely cause.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: mentions AGENTS.md.

This is whoamiTM/bi-mcp's own configuration. It tells Claude Code how to work on bi-mcp 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 bi-mcp configures →

Reuse

Borrowing it

Nothing to install: this file belongs to whoamiTM/bi-mcp. 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/whoamiTM/bi-mcp/main/.claude/skills/bi-troubleshoot/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/whoamiTM/bi-mcp

Made for: Claude Code.

Wrote this? Show the measurements

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README.md
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Your own site · 80×15
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Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 943 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00053 $0.00943
Opus 5 $0.00026 $0.00472
Sonnet 5 $0.00011 $0.00189
Haiku 4.5 $0.00005 $0.00094

Measured 11d ago against content hash 3a2e34675f7c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

bi-troubleshoot 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 11d 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/skills/bi-troubleshoot/SKILL.md · 110 lines

How it starts

The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.

bi-troubleshoot — alert pipeline diagnosis

Use this when the user reports an alert problem on a specific camera — missing alerts, spurious alerts, wrong classification, alerts at the wrong times of day. Do NOT use for connectivity / PTZ / recording issues; those need different surfaces.

Step 1 — Confirm the symptom in data

bi_list_alerts(camera="<short>", limit=50)

Look at the time distribution, AI memo, and zone hits. Don't trust the user's framing alone — they may have miscounted, or the issue may be different from how they described it.

If they gave you a time range:

bi_list_alerts(camera="<short>", startdate=<unix>, enddate=<unix>, limit=200)

If you need clip context (was it recording? what resolution?):

bi_list_clips(camera="<short>", view="alerts", limit=20)

Step 2 — Read top-level config

bi_get_camera_config(short="<short>")

Note sense, contrast, recmode, aizones, profile/schedule flags. The _note field tells you whether you got the admin (deep) or fallback (shallow) view.

Step 3 — Drill into what camconfig doesn't expose

Pick the area that matches the symptom:

Symptom bi_get_reg key_path
Wrong AI classification / thresholds AI\\<profile> (smartconf, smartlabels, smartzones)
Trigger zones look wrong Motion\\<profile> (maskbits_*, objmaxpercent10)
Alerts not firing during PTZ preset PTZ\\Presets (noalerts flag per preset)
Dahua IVS not reaching BI camevents (ONVIF event handlers)
Wrong action (no email/webhook) Alerts\\OnTrigger

If bi_get_reg returns meta.stale: true, stop and ask the user to re-export the camera before continuing — stale data will lead you astray.

Step 4 — Form ONE hypothesis

Read the full file on GitHub · 110 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. 11d ago First seen · 110 lines · 53 tokens per session scan A 3a2e34675f7c

Subscribe to this mod's changes

bi-troubleshoot is a skill published in the GitHub repository whoamiTM/bi-mcp (2 stars, last pushed 12d ago), licensed MIT. It adds 53 tokens to every session and 943 once invoked, about $0.0003 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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