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 skills add hamzabellouch/agent-skills --skill academic-nature-nature-readergit clone --depth 1 https://github.com/hamzabellouch/agent-skillsWrote 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/hamzabellouch/agent-skills/academic-nature-nature-reader)<a href="https://agentmods.dev/skills/hamzabellouch/agent-skills/academic-nature-nature-reader"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/academic-nature-nature-reader/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/skills/hamzabellouch/agent-skills/academic-nature-nature-reader"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/academic-nature-nature-reader.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 | $0.00193 | $0.01016 |
| Opus 5 | $0.00097 | $0.00508 |
| Sonnet 5 | $0.00039 | $0.00203 |
| Haiku 4.5 | $0.00019 | $0.00102 |
Grade A, and why
nature-reader 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.
This is a copy
92% identical to nature-reader — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Full-Paper Markdown Reader — Router
This skill is split into two layers:
- A static layer under
static/that holds versioned, reusable content fragments (core principles, the reading workflow, the output contract, and per-source-format extraction guidance). - A dynamic layer (this file plus
manifest.yaml) that detects the request's source format and loads only the fragments needed for the current job.
Do not try to apply the reading logic from memory or from this router. Always load fragments from disk as described below.
Routing protocol
Follow these five steps every time the skill is invoked.
1. Load the manifest and the core layer
Read manifest.yaml. It declares the source_format axis, the allowed values, and the file paths each value maps to.
Also read every file listed under always_load. These hold the core principles, the reading workflow, and the output contract that apply to every reading job, plus the shared Terminology Ledger used to build the recurring-term table.
2. Detect the source format
Decide the source_format value using the manifest's detect: hint and the user's input:
pdf-text— selectable-text PDF. Default.scanned-pdf— image-only or OCR-required PDF.html— publisher or preprint HTML page.doi-arxiv— a bare DOI or arXiv link that must be resolved first.pasted-text— pasted prose or notes with no retrievable original layout.
State the detected value in one short line to the user before processing, so they can correct you cheaply. A source may map to more than one value (for example a DOI that resolves to a PDF); load the resolution fragment first, then the fragment for the resolved artifact.
3. Load the matching fragment(s)
Read the file mapped for the detected source_format. Do not read every fragment in static/. Load only what step 2 selected.
4. Build the reader using the loaded material
Apply the loaded fragments in this priority order:
What ships with it
16 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- evals/evals.json 1.8 KB
- manifest.yaml 2.0 KB
- README_EN.md 2.0 KB
- README.md 1.7 KB
- references/article-anatomy.md 3.3 KB
- references/figure-extraction.md 2.0 KB
- references/grounding-rules.md 1.9 KB
- references/output-spec.md 3.7 KB
- static/core/output-contract.md 1.2 KB
- static/core/principles.md 2.9 KB
- static/core/workflow.md 4.0 KB
- static/fragments/source/doi-arxiv.md 1.1 KB
- static/fragments/source/html.md 1011 B
- static/fragments/source/pasted-text.md 1.0 KB
- static/fragments/source/pdf-text.md 863 B
- static/fragments/source/scanned-pdf.md 899 B
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 · 70 lines · 193 tokens per session scan A b52745af2f1d
nature-reader is a skill published in the GitHub repository hamzabellouch/agent-skills (4 stars, last pushed 1mo ago), licensed MIT. It adds 193 tokens to every session and 1,016 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to nature-reader, differing in 8 lines, and is treated as a copy.
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