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 d-o-hub/github-template-ai-agents --skill web-search-researchergit clone --depth 1 https://github.com/d-o-hub/github-template-ai-agentsWrote 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/d-o-hub/github-template-ai-agents/web-search-researcher)<a href="https://agentmods.dev/skills/d-o-hub/github-template-ai-agents/web-search-researcher"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/web-search-researcher/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/d-o-hub/github-template-ai-agents/web-search-researcher"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/web-search-researcher.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 | $0.00070 | $0.01368 |
| Opus 5 | $0.00035 | $0.00684 |
| Sonnet 5 | $0.00014 | $0.00274 |
| Haiku 4.5 | $0.00007 | $0.00137 |
Grade A, and why
web-search-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 10d 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 — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Web Search Research
Find accurate, relevant information from web sources.
When to Use
- Modern information not in training data
- Official documentation for APIs/libraries
- Best practices and recommendations
- Technical solutions
- Technology comparisons
Date Context
CRITICAL: Check <env> for current date.
- Include current year in searches
- Evaluate freshness (12-18 months = recent)
Core Process
1. Analyze Query
Identify key terms, source types, search angles.
2. Strategic Searches
- Start broad, refine
- Multiple variations
- Site-specific searches
3. Fetch Content
- WebFetch promising results
- Prioritize official docs
- Note publication dates
4. Synthesize
- Organize by relevance
- Include quotes with links
- Note gaps/conflicts
Search Strategies
API Documentation
"[library] official docs [feature]"
site:docs.stripe.com webhook
Best Practices
"Rust async" best practices 2026
Technical Solutions
"tokio panic" redb write
site:github.com tokio spawn_blocking
Comparisons
"redb vs sled" performance
Progressive Strategy
Round 1 (5 min): 1-2 broad searches. If official docs → stop.
Round 2 (10 min): 2-3 specific searches, fetch 2-3 sources. If consensus → stop.
Round 3 (15 min): Fill gaps, synthesize.
Rule: Most complete in Round 2.
Source Priority
⭐⭐⭐ Fetch First: Official docs, GitHub maintainers, recent experts
⭐⭐ Fetch If Needed: Expert blogs, high-vote SO, conference talks
⭐ Skip: Generic tutorials, old posts, no author
🚫 Never: AI farms, aggregators
Search Operators
| Operator | Example |
|---|---|
"exact" |
"async runtime" |
-term |
rust -game |
site: |
site:docs.rs |
after: |
async after:2024 |
Output Format
## Summary
[2-3 sentences]
## Findings
### [Source 1]
**Source**: [Link]
**Key Info**:
- Quote/finding
### [Source 2]
**Source**: [Link]
**Key Info**:
- Finding
## Resources
- [Link] - Description
## Gaps
[What not found]
What ships with it
2 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.
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.
- 10d ago First seen · 245 lines · 70 tokens per session scan A 38e06f73dcf0
web-search-researcher is a skill published in the GitHub repository d-o-hub/github-template-ai-agents (2 stars, last pushed yesterday), licensed MIT. It adds 70 tokens to every session and 1,368 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 2026-08-31.
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