Borrowing it
Nothing to install: this file belongs to sani-savaliya/parallax. 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/sani-savaliya/parallax/main/CLAUDE.mdgit clone --depth 1 https://github.com/sani-savaliya/parallaxWrote 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/sani-savaliya/parallax/claude-md)<a href="https://agentmods.dev/instructions/sani-savaliya/parallax/claude-md"><img src="https://agentmods.dev/badge/instructions/sani-savaliya/parallax/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/sani-savaliya/parallax/claude-md"><img src="https://agentmods.dev/badge/instructions/sani-savaliya/parallax/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 | $0.00744 | $0.00744 |
| Opus 5 | $0.00372 | $0.00372 |
| Sonnet 5 | $0.00149 | $0.00149 |
| Haiku 4.5 | $0.00074 | $0.00074 |
Grade A, and why
parallax 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 — 30 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parallax — project instructions
Render-in-the-loop self-verification primitive for coding agents + a factorial-decomposition study of why it works. Part of the SunnyCode workspace.
Status
M1 (library MVP) usable. The crosscheck primitive runs end-to-end with two adapters (SQL-result-shape, regex-highlight), an offline heuristic critic + an Anthropic vision critic, a CLI (parallax), and an MCP server (parallax-mcp). The full design package lives in docs/; start from docs/TASKS.md (TDD-first, split into M1 library MVP and M2 study). Read docs/EVAL.md before touching any eval code and docs/RED-TEAM.md to understand why the design is shaped the way it is. M2 (the factorial study) is not started.
Names & handles
- Brand: Parallax · PyPI/npm dist:
parallax-verify· import package:parallax· repo:sani-savaliya/parallax - API function:
crosscheck(artifact, render_fn)(kept deliberately — only the product name changed away from the collision-heavy "crosscheck"). - Domains available if wanted: parallaxverify.com, parallax.sh.
Build & test (planned)
- Language: Python. Package layout
src/parallax/,tests/,pyproject.toml,ruff+mypy. - TDD is mandatory — tests before implementation, 80%+ coverage (unit + integration + the eval harness has its own fixtures).
- Run tests from this project root (see docs/TASKS.md for exact commands once scaffolded).
Key design invariants (do not violate)
- Single multimodal model across all model arms — never a text-LLM vs a separate VLM (that's a sixth confound).
- The feature set
Fshown to model arms contains no verdict flags — only raw/derived quantities. All thresholding lives in the deterministicA5arm, whose thresholds are disjoint from the defect-generating parameters. (This is the leak that collapsed v1.) - Compute is measured, not gated — never abort a run on token-equality (selection on the dependent variable). Match on cost + passes + FLOP proxies; report them.
- Symmetrize tuning effort, never read-back outcome — capping the render to what the text reaches is mediator/collider adjustment that erases real effects.
- Renders sandbox-safe: DuckDB with httpfs/COPY/external-file access disabled, timeouts, no network; beware the subprocess socket-monkeypatch bypass (see docs/ARCHITECTURE.md).
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 · 30 lines · 744 tokens per session scan A 31b2c360daee
parallax CLAUDE.md is an instructions file published in the GitHub repository sani-savaliya/parallax (0 stars, last pushed 1mo ago), licensed MIT. It adds 744 tokens to every session, about $0.0037 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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