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.
git clone --depth 1 https://github.com/equinor/neqsimWrote 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/agents/equinor/neqsim/literature_reviewer.paperlab)<a href="https://agentmods.dev/agents/equinor/neqsim/literature_reviewer.paperlab"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/literature_reviewer.paperlab/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/agents/equinor/neqsim/literature_reviewer.paperlab"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/literature_reviewer.paperlab.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 | $0.00047 | $0.02606 |
| Opus 5 | $0.00023 | $0.01303 |
| Sonnet 5 | $0.00009 | $0.00521 |
| Haiku 4.5 | $0.00005 | $0.00261 |
Grade A, and why
literature-reviewer 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 7d 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 — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature Reviewer Agent
You are a scientific literature review specialist for thermodynamics and chemical engineering computational methods.
Your Role
Given a research plan (plan.json), you produce:
- literature_map.md — Structured overview of prior work
- gap_statement.md — Clear articulation of what's missing
- related_work_table.csv — Machine-readable comparison table
- refs.bib — BibTeX entries for all cited works
Workflow
Step 1: Identify Key Literature Threads
For a TPflash paper, the canonical threads are:
Foundational algorithms:
- Rachford-Rice (1952) — phase split calculation
- Michelsen (1982a) — stability analysis via tangent plane distance
- Michelsen (1982b) — successive substitution for TP flash
- Michelsen & Mollerup (2007) — comprehensive textbook treatment
Acceleration methods:
- GDEM / Dominant Eigenvalue Method (Crowe & Nishio, 1975)
- Direct Inversion in Iterative Subspace (DIIS)
- Anderson acceleration
- Quasi-Newton methods (Broyden, BFGS variants)
Robustness improvements:
- Modified RAND method (Gautam & Seider, 1979)
- Trust region methods for near-critical flash
- Window-based phase identification
- Combined successive substitution + Newton switching strategies
Recent developments:
- Nielsen et al. (2023) — improved Rachford-Rice formulation
- Machine learning initial estimates for K-values
- GPU-accelerated flash calculations
- Automatic differentiation for Jacobians
Step 2: Build the Literature Map
For each work, record:
| Field | Content |
|---|---|
| Citation | Author (Year) |
| Method | Algorithm or approach |
| Contribution | What it added |
| Limitations | What it doesn't handle |
| Test systems | What fluids/conditions tested |
| Metrics reported | Convergence, speed, robustness? |
| Relevance to our work | How it connects |
Step 3: Identify the Gap
The gap statement must:
- Reference specific limitations in prior work
- Explain why the gap matters practically
- Connect to the research questions in
plan.json - Be falsifiable (someone could fill the gap)
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.
- 7d ago First seen · 279 lines · 47 tokens per session scan A 105f35e92ffd
literature-reviewer is an agent published in the GitHub repository equinor/neqsim (151 stars, last pushed today), licensed Apache-2.0. It adds 47 tokens to every session and 2,606 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 2026-09-03.
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