Borrowing it
Nothing to install: this file belongs to EvoTestOps/LogLead. 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/EvoTestOps/LogLead/main/CLAUDE.mdgit clone --depth 1 https://github.com/EvoTestOps/LogLeadWrote 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/evotestops/loglead/claude-md)<a href="https://agentmods.dev/instructions/evotestops/loglead/claude-md"><img src="https://agentmods.dev/badge/instructions/evotestops/loglead/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/evotestops/loglead/claude-md"><img src="https://agentmods.dev/badge/instructions/evotestops/loglead/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 | $0.01065 | $0.01065 |
| Opus 5.5 | $0.00426 | $0.00426 |
| Sonnet 5.5 | $0.00213 | $0.00213 |
| Haiku 4.5 | $0.00106 | $0.00106 |
Grade A, and why
LogLead 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 1mo 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
Guidance for coding agents working in this repo.
LogLead (Log Loader, Enhancer, Anomaly Detector): benchmarks log anomaly detection algorithms/
representations via ~10 dataset loaders, log representation enhancers, and anomaly detection
classifiers, independently swappable. Also used as a backend library by sibling projects LogDelta
and VisualLogAnalyzer — changes to public APIs in loglead/ can affect them. Data is Polars
DataFrames throughout (not Pandas).
Build & Test
- Python 3.9–3.12 via
uv.uv run <script>syncs env and installslogleadeditable — no separate install step. .env(LOG_DATA_PATH) only needed for "bring your own full dataset" scripts; quick demos use bundled sample parquet files instead.LOG_DATA_PATH(.env) androot_folder(dataset YAML config) are independent, unlinked settings — keeping them in sync is on you.- Smoke tests:
uv run demo/HDFS_samples.py,uv run demo/TB_samples.py. - Full suite (downloads real datasets, ~30 min):
uv run tests/main.py, chainingdownloader/download_data.pythentests/loaders.py/enhancers.py/anomaly_detectors.py. Plain scripts, not pytest — read console output forMISMATCH!/errors. Run a stage directly to iterate once its input parquet exists in<root_folder>/test_data/. Other dataset families via--config tests/datasets_*.yml. uv run tests/log_file_detection.py --config <cfg>— checksAutoLoaderformat detection without loading full data; covers datasets too large to load.- MCP server tests (needs
uv sync --extra mcp):uv run tests/mcp/server.py; perf grid:uv run tests/mcp/benchmark.py(seetests/mcp/PERFORMANCE.md). - Downloader:
uv run downloader/download_data.py [--config <cfg>]. Full set ~7GB download / ~104GB unzipped — check disk space first. - No linter, formatter, or CI configured — don't invent one unless asked.
Core Architecture
Pipeline: Loader → Enhancer → AnomalyDetector, connected via Polars DataFrames with a shared column-naming convention:
m_*— raw columns from a Loader (e.g.m_message,m_timestamp).e_*— event-level columns fromEventLogEnhancer(e.g.e_words,e_event_drain_id).seq_*/ unprefixed — sequence-level columns fromSequenceEnhancer.normal/anomaly— boolean labels;BaseLoader.add_ano_col()derives whichever is missing.
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.
- 1mo ago Changed · -27 tokens per session a32c29d98e04
- 1mo ago Changed · +1 lines · +13 tokens per session 38fd6dc0e5e8
- 1mo ago Changed · +1 lines · +75 tokens per session aa854b3ddfd8
- 1mo ago Changed · -495 lines · -9,156 tokens per session fc7853462928
- 2mo ago Changed · +8 lines · +186 tokens per session 16a690a8a312
- 2mo ago First seen · 531 lines · 9,974 tokens per session scan A fbcfce744d7e
LogLead CLAUDE.md is an instructions file published in the GitHub repository EvoTestOps/LogLead (33 stars, last pushed 1mo ago), licensed MIT. It adds 1,065 tokens to every session, about $0.0043 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.
LogLead CLAUDE.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| LogLead CLAUDE.mdEvoTestOps/LogLead | Instructions file | 33 | 1mo ago | MIT | A | 1,065 | Claude Code |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,649 | GitHub Copilot |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| vscode ai-customization.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 1,907 | GitHub Copilot |