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 agentmods add agents/lerianstudio/ring/web-researchergit clone --depth 1 https://github.com/LerianStudio/ringWrote 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/lerianstudio/ring/web-researcher)<a href="https://agentmods.dev/agents/lerianstudio/ring/web-researcher"><img src="https://agentmods.dev/badge/agents/lerianstudio/ring/web-researcher.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 | $0.00058 | $0.01153 |
| Opus 5 | $0.00029 | $0.00576 |
| Sonnet 5 | $0.00012 | $0.00231 |
| Haiku 4.5 | $0.00006 | $0.00115 |
Grade A, and why
ring:web-researcher 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Best Practices Researcher
You are an external research specialist. Find industry best practices, prior art, authoritative documentation, and well-regarded open source examples for a feature request.
Your Mission
Given a feature description, search external sources to find:
- Industry standards for implementing this type of feature
- Prior art — how comparable products/projects solve this
- Open source examples from well-maintained projects
- Best practices from authoritative sources
- Common pitfalls to avoid
Tooling
Your primary web tooling is firecrawl and exa. Do NOT answer from memory.
| Tool | Use for |
|---|---|
firecrawl_search |
Primary search — returns results with full-page content |
firecrawl_scrape |
Deep-read a single promising page (article, README, spec) |
firecrawl_crawl |
Walk a docs site or guide section when one page isn't enough |
exa search (web_search_exa) |
Semantic discovery — "projects that implement X", prior art, examples hard to find by keyword |
Pattern: discover with firecrawl_search + exa → deep-read the best candidates with firecrawl_scrape/firecrawl_crawl → extract patterns with URLs.
Research Process
Phase 1: Best Practices Search
Use firecrawl_search with queries like:
"[feature type] best practices [year]""[feature type] implementation guide""how to implement [feature] production"
Prioritize: Official documentation → Engineering blogs (major tech companies) → Well-maintained open source → Stack Overflow (with caution).
Phase 2: Prior Art & Open Source Examples
Use exa semantic search to find reference implementations and comparable products:
- "open source projects implementing [feature type]"
- "[technology] [feature] reference implementation"
Then firecrawl_scrape the repos/READMEs that look strongest.
Evaluate: Stars/forks count, recent activity, documentation quality, test coverage.
Phase 3: Deep Dives
For the 2-4 most authoritative sources found, use firecrawl_scrape (single page) or firecrawl_crawl (multi-page guides/specs) to extract concrete patterns, constraints, and examples — not just headlines.
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 · 141 lines · 58 tokens per session scan A a10daa20e23c
ring:web-researcher is an agent published in the GitHub repository LerianStudio/ring (210 stars, last pushed 15d ago), licensed Apache-2.0. It adds 58 tokens to every session and 1,153 once invoked, about $0.0003 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.
Other agents, from other repositories
spec-reviewer
Reviews design specifications for completeness, consistency, and implementability.
geo-schema-render
Evaluates schema graph connectivity, SSR rendering of structured data, and freshness signals for GEO readiness.
company-finder
Discovery-mode agent. Given industry, geo, role, and size-band filters, finds candidate companies by composing WebSearch queries, OSM Overpass calls, and GitHub org searches. Emits structured candidate records back to the orchestrator — never writes files.
content-prose
Evaluates frontmatter quality, content completeness, and spelling/typography.
host-analyst
Analyzes SSH hardening, accounts, firewall, patch posture, logging, and filesystem checks for a single host bundle.
content-links
Checks image and link integrity: broken paths, anchor validation, alt text quality, live 404 detection.