Borrowing it
Nothing to install: this file belongs to bdog720/oraclarr. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/bdog720/oraclarr/main/CLAUDE.mdgit clone --depth 1 https://github.com/bdog720/oraclarrWrote 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/instructions/bdog720/oraclarr/claude-md)<a href="https://agentmods.dev/instructions/bdog720/oraclarr/claude-md"><img src="https://agentmods.dev/badge/instructions/bdog720/oraclarr/claude-md/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/instructions/bdog720/oraclarr/claude-md"><img src="https://agentmods.dev/badge/instructions/bdog720/oraclarr/claude-md.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 | $0.04236 | $0.04236 |
| Opus 5.5 | $0.01694 | $0.01694 |
| Sonnet 5.5 | $0.00847 | $0.00847 |
| Haiku 4.5 | $0.00424 | $0.00424 |
Grade A, and why
oraclarr 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 6d 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 — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Oraclarr
Read-only-by-default diagnostic MCP server (Python/FastMCP) for a self-hosted arr media
stack. Answers operational "why" questions by aggregating across services.
Phased toward full read+write coverage. Reads are the default; writes are opt-in
through one gated tool, start_job (since 2.0.0).
Architecture
Layered. Clients talk to services; tools answer questions. Keep the boundary clean: a tool composes clients, never embeds HTTP/auth detail.
config.py ORACLARR_* env (parse_env) over optional YAML -> typed Config (load_settings)
registry.py instance.type -> client class; build_clients(cfg)
clients/ async adapters: base, arr, prowlarr, qbittorrent, tdarr, profilarr, jellyfin, cleanuparr,
netdata (httpx), truenas (JSON-RPC over WebSocket),
docker (httpx, read-only socket proxy). Clients are read-only; the only writes are
the command/scan POSTs that `start_job` sends through the plan flow
tools/ outcome tools; each composes clients via fan_out/probe
guards.py per-tool risk+domain tags; toolset filter; write gate
auth.py HTTP bearer-token check (ORACLARR_HTTP_TOKEN); startup refuses writes on http without it
plans.py in-memory single-use plans (10 min) for the two-step write flow
audit.py `audit event=<planned|executed|refused|failed|unknown>` log lines for every write event
tools/jobs_write.py start_job: dry-run builds a plan, execute rebuilds it and compares fingerprints
budget.py per-call deadline ContextVar; probe() reads it (partial results on timeout)
redact.py Redactor (config secrets + key patterns) + log record-factory redaction
call_guard.py guarded(): deadline, backstop (budget+2s), output cap, redaction, Any return
server.py FastMCP app; registers only tools whose domain is in cfg.server.toolsets
models.py InstanceResult envelope; MediaRef (carries tvdb/tmdb/imdb ids)
v1 services: sonarr, sonarr-anime, radarr, sportarr, prowlarr, qbit,
tdarr, profilarr, jellyfin, cleanuparr, netdata, truenas, docker. Tools: stack_health, get_queues, diagnose,
explain_decision, get_quality_config, get_history, get_wanted,
search_media, get_indexers, get_transcodes, get_upcoming, get_library, get_cleanup, get_host (toolset host), get_containers
(toolset containers), get_jobs, start_job (the only write tool; registered only when writes are enabled).
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.
- 6d ago Changed · +4 lines · +77 tokens per session 17d97e930024
- 8d ago First seen · 234 lines · 4,159 tokens per session scan A c3e2edf2fef5
oraclarr CLAUDE.md is an instructions file published in the GitHub repository bdog720/oraclarr (0 stars, last pushed 7d ago), licensed Apache-2.0. It adds 4,236 tokens to every session, about $0.0169 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 2026-10-30.
oraclarr CLAUDE.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| oraclarr CLAUDE.mdbdog720/oraclarr | Instructions file | 0 | 7d ago | Apache-2.0 | A | 4,236 | Claude Code |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
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| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |