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 YuanyuanMa03/academic-research-skills --skill wos-navigate-pagesgit clone --depth 1 https://github.com/YuanyuanMa03/academic-research-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/yuanyuanma03/academic-research-skills/wos-navigate-pages)<a href="https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/wos-navigate-pages"><img src="https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/wos-navigate-pages/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/yuanyuanma03/academic-research-skills/wos-navigate-pages"><img src="https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/wos-navigate-pages.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 | $0.00026 | $0.00839 |
| Opus 5.5 | $0.00010 | $0.00336 |
| Sonnet 5.5 | $0.00005 | $0.00168 |
| Haiku 4.5 | $0.00003 | $0.00084 |
Grade A, and why
wos-navigate-pages scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WoS Navigate Pages
Load a specific page of results from the current WoS search.
Steps
The two approaches below each count as one step.
Approach A: URL-based (when browser is on a results page)
The results URL follows the pattern:
/wos/woscc/summary/{session-uuid}/{sort}/{page-number}
Modify the page number in the URL and navigate. Then extract via evaluate_script with DOM selectors. Uses 2 tool calls.
Approach B: API-based (preferred, 1 tool call)
Re-run the search API with retrieve.first offset:
async () => {
const sid = performance.getEntriesByType('resource')
.filter(r => r.name.includes('SID='))
.map(r => r.name.match(/SID=([^&]+)/)?.[1])
.filter(Boolean)[0] || '';
const page = {TARGET_PAGE}; // 1-based
const perPage = 50;
const first = (page - 1) * perPage + 1;
const response = await fetch(`/api/wosnx/core/runQuerySearch?SID=${sid}`, {
method: 'POST',
headers: { 'Content-Type': 'text/plain;charset=UTF-8', 'Accept': 'application/x-ndjson' },
body: JSON.stringify({
"product": "WOSCC",
"searchMode": "general",
"viewType": "search",
"serviceMode": "summary",
"search": {
"mode": "general",
"database": "WOSCC",
"query": [{SAME_QUERY_AS_ORIGINAL_SEARCH}],
"editions": [{SAME_EDITIONS}]
},
"retrieve": {
"first": first,
"count": perPage,
"history": false,
"jcr": true,
"sort": "{SAME_SORT}",
"analyzes": [],
"locale": "en"
},
"eventMode": null
})
});
const text = await response.text();
const lines = text.trim().split('\n').map(l => { try { return JSON.parse(l); } catch(e) { return null; } }).filter(Boolean);
const searchInfo = lines.find(l => l.key === 'searchInfo')?.payload;
const recordsData = lines.find(l => l.key === 'records')?.payload;
let records = [];
if (recordsData) {
records = Object.entries(recordsData).map(([idx, rec]) => ({
idx: first + parseInt(idx) - 1,
wosId: rec.colluid,
title: rec.titles?.item?.en?.[0]?.title || '',
authors: rec.names?.author?.en?.filter(Boolean).map(a => a.wos_standard).join('; ') || '',
source: rec.titles?.source?.en?.[0]?.title || '',
year: rec.pub_info?.pubyear || '',
doi: rec.doi || '',
citations: rec.citation_related?.counts?.WOSCC || 0
}));
}
return { status: 'ok', page, totalResults: searchInfo?.RecordsFound || 0, records };
}
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.
- today First seen · 98 lines · 26 tokens per session scan A 26f1feb857b2
wos-navigate-pages is a skill published in the GitHub repository YuanyuanMa03/academic-research-skills (75 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 839 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-29.
Other skills, from other repositories
agent-platform-tuning
Agent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use agent-platform-deploy), or managing serving endpoints (use agent-platform-endpoint-management).
gke-compute-classes
Configures, optimizes, and troubleshoots GKE ComputeClasses. Use when configuring Spot VMs with on-demand fallback, targeting specific accelerators (GPUs/TPUs) or machine families, restricting ComputeClass access, or debugging pending pods related to node pool auto-creation. Do not use for cluster-level Node Auto…
gke-alert-configuration
Configures alerting policies in Terraform for Google Kubernetes Engine (GKE) clusters, workloads, and services using PromQL and Google Cloud Managed Service for Prometheus. Use when writing, analyzing, validating, or deploying Terraform alerting policies to monitor GKE service latency, traffic, error rates using…
secops-detection-engineering
Author, validate, test, and deploy YARA-L 2.0 detection rules and evaluate end-to-end detection coverage gaps in Google SecOps. Use when writing new detection rules, tuning existing rules, validating syntax, testing logic against historical telemetry, or evaluating detection coverage against threat intelligence blogs…
application-design-center-design-deploy
Processes GCP infrastructure design and deployment workflows within Application Design Center (ADC). Use when: - Designing GCP infrastructure with Terraform. - Validating local HCL. - Performing best-practice plan scans. - Importing templates to Application Design Center (ADC). - Deploying templates. - Troubleshooting…
cloud-run-basics
Manages Cloud Run services, jobs, and worker pools. Use when you need to deploy applications responding to HTTP requests (services), run event-triggered or scheduled tasks (jobs), or handle always-on pull-based background processing (worker pools).