Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/piebald-ai/splitrail/new-analyzernpx skills add Piebald-AI/splitrail --skill new-analyzergit clone --depth 1 https://github.com/Piebald-AI/splitrailWrote 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/skills/piebald-ai/splitrail/new-analyzer)<a href="https://agentmods.dev/skills/piebald-ai/splitrail/new-analyzer"><img src="https://agentmods.dev/badge/skills/piebald-ai/splitrail/new-analyzer.svg" alt="Measured on agentmods" 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 | $0.00035 | $0.00344 |
| Opus 5 | $0.00017 | $0.00172 |
| Sonnet 5 | $0.00007 | $0.00069 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
new-analyzer 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 5d 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.
What it actually says
Adding a New Analyzer
Splitrail tracks token usage from AI coding agents. Each agent has its own "analyzer" that discovers and parses its data files.
Checklist
- Add variant to
Applicationenum insrc/types.rs - Create
src/analyzers/{agent_name}.rsimplementingAnalyzertrait fromsrc/analyzer.rs - Export in
src/analyzers/mod.rs - Register in
src/main.rs - Add tests in
src/analyzers/tests/{agent_name}.rs, export insrc/analyzers/tests/mod.rs - Update README.md
- (Optional) Add model pricing to
src/models.rsif agent doesn't provide cost data
Test fixtures go in src/analyzers/tests/source_data/. See src/types.rs for message and stats types.
VS Code Extensions
Use discover_vscode_extension_sources() and get_vscode_extension_tasks_dirs() helpers from src/analyzer.rs.
Reference Analyzers
- Simple JSONL CLI:
src/analyzers/pi_agent.rs,src/analyzers/piebald.rs - VS Code extension:
src/analyzers/cline.rs,src/analyzers/roo_code.rs - Complex with dedup:
src/analyzers/claude_code.rs - External data dirs:
src/analyzers/opencode.rs
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.
- 5d ago First seen · 32 lines · 35 tokens per session scan A 0ffd12568746
new-analyzer is a skill published in the GitHub repository Piebald-AI/splitrail (218 stars, last pushed today), licensed MIT. It adds 35 tokens to every session and 344 once invoked, about $0.0002 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 2026-08-30.
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