Borrowing it
Nothing to install: this file belongs to assister-xyz/quality-oracle. 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/assister-xyz/quality-oracle/main/CLAUDE.mdgit clone --depth 1 https://github.com/assister-xyz/quality-oracleWrote 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/assister-xyz/quality-oracle/claude-md)<a href="https://agentmods.dev/instructions/assister-xyz/quality-oracle/claude-md"><img src="https://agentmods.dev/badge/instructions/assister-xyz/quality-oracle/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/assister-xyz/quality-oracle/claude-md"><img src="https://agentmods.dev/badge/instructions/assister-xyz/quality-oracle/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 | $0.00906 | $0.00906 |
| Opus 5 | $0.00453 | $0.00453 |
| Sonnet 5 | $0.00181 | $0.00181 |
| Haiku 4.5 | $0.00091 | $0.00091 |
Grade A, and why
quality-oracle 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 9d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Laureum.ai (Quality Oracle)
Part of assisterr-workflow. See
../assisterr-workflow/CLAUDE.mdfor full workflow, sizing, spec lifecycle, memory entities, and agent routing.
Project Context
- Port: 8002
- Stack: FastAPI + Motor (MongoDB) + Redis
- Brand: Laureum.ai (standard: AQVC — Agent Quality Verifiable Credential)
- MongoDB prefix:
quality__(collections: evaluations, scores, score_history, attestations, question_banks, api_keys) - Redis prefix:
qo:(score cache, badge cache, attestation verify cache, rate limits) - LLM Judge: Multi-provider (Cerebras, Groq, Gemini, DeepSeek, OpenAI, OpenRouter, Mistral) with ConsensusJudge (2-judge parallel + tiebreaker)
- Domain agent:
32-implement-pyhandles this repo
Architecture
3-level evaluation pipeline:
- Level 1 (Manifest): Schema completeness, descriptions, input schemas
- Level 2 (Functional): MCP SSE connection → list tools → generate test cases → call tools → LLM judge responses
- Level 3 (Domain Expert): Calibrated question bank with weighted scoring
6-axis scoring: accuracy(35%), safety(20%), process_quality(10%), reliability(15%), latency(10%), schema_quality(10%). Production correlation: POST /v1/feedback → GET /v1/correlation/{target_id} (anti-sandbagging, confidence adjustment).
JWT attestation via Ed25519 (AQVC format). MCP SDK SSE + Streamable HTTP dual transport. A2A v0.3 compliant Agent Card. Webhook-first async delivery for Level 2+.
x402 payment layer: Level 1 free, Level 2 $0.01, Level 3 $0.05 (base). Tier discounts: developer 20%, team 40%, marketplace 60%. Tokens: USDC + SOL on Solana. X-Payment header with tx_sig:token:network format. GET /v1/pricing for pricing table.
Running Locally
source .venv/bin/activate && unset GROQ_API_KEY && python3 -m uvicorn src.main:app --host 0.0.0.0 --port 8002 --reload
Important: Always unset GROQ_API_KEY before starting — a shell env variable overrides the .env key rotation pool.
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.
- 9d ago First seen · 76 lines · 906 tokens per session scan A 23fe5b471faa
quality-oracle CLAUDE.md is an instructions file published in the GitHub repository assister-xyz/quality-oracle (0 stars, last pushed 4mo ago), licensed MIT. It adds 906 tokens to every session, about $0.0045 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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