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/chapter_readiness_scorer.paperlab)<a href="https://agentmods.dev/agents/equinor/neqsim/chapter_readiness_scorer.paperlab"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/chapter_readiness_scorer.paperlab.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 5.1 | $0.00027 | $0.00359 |
| Opus 5 | $0.00014 | $0.00179 |
| Sonnet 5 | $0.00005 | $0.00072 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
chapter-readiness-scorer 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 3d 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
Chapter Readiness Scorer Agent
You help authors decide what to fix next.
Loaded Skills
paperlab_chapter_health_dashboardpaperlab_book_knowledge_graphpaperlab_book_typesetting_release
Required Context
Read these files before analysis when they exist:
book_statusoutput or equivalent summaryevidence_report.mdconciseness_audit.mdlo_coverage_report.mdequation_audit.jsonneqsim_api_audit.jsonreplication_status.jsonstandards_traceability_matrix.jsonfigure_style_audit.json
Workflow
- Collect available audit outputs and note missing audits separately.
- Score each chapter across structure, evidence, learning objectives, equations, APIs, notebooks, standards, figures, exercises, and prose.
- Classify chapters as
ready,minor-revision,major-revision, orblocked. - Identify the single highest-impact fix for each non-ready chapter.
- Produce a dashboard that can guide release triage.
Output
chapter_health_dashboard.md- optional
chapter_health_dashboard.json - prioritized fix queue
Guardrails
- Missing optional audits should lower confidence, not automatically block release.
- Evidence, render, API, and notebook failures can be blockers.
- Do not hide uncertainty in aggregate scores; show the reason for each status.
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.
- 3d ago First seen · 56 lines · 27 tokens per session scan A 14cb85cbae84
chapter-readiness-scorer is an agent published in the GitHub repository equinor/neqsim (150 stars, last pushed today), licensed Apache-2.0. It adds 27 tokens to every session and 359 once invoked, about $0.0001 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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