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 skills/firecrawl/web-agent/deep-researchnpx skills add firecrawl/web-agent --skill deep-researchgit clone --depth 1 https://github.com/firecrawl/web-agentWhat 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 | $0.00027 | $0.00253 |
| Opus 5 | $0.00014 | $0.00127 |
| Sonnet 5 | $0.00005 | $0.00051 |
| Haiku 4.5 | $0.00003 | $0.00025 |
Grade A, and why
deep-research 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 2d 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
Deep Research
Search Strategy
- Break the topic into 3-5 distinct angles
- 2-3 queries per angle using different terminology
- Use
site:operator for targeted searches (e.g.site:arxiv.org,site:github.com) - Include official, comparison, and review-oriented queries
- Aim for 5-10 unique, high-quality sources
Extraction
- Scrape each source with a targeted query parameter -- don't dump full pages into context
- Extract: key claims, data points, dates, attributed quotes
- Record author, publication, date, and URL for every source
Fact-Checking
- Cross-reference claims across 2+ sources
- Flag single-source claims explicitly
- Assign confidence: high (3+ sources agree), medium (2), low (1 or conflicting)
- Include contrarian viewpoints -- don't confirmation-bias the results
Output
- Structure by subtopic, not by source
- Inline citations for every claim
- Call formatOutput with the structured data
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.
- 2d ago First seen · 31 lines · 27 tokens per session scan A eb83c5387166
deep-research is a skill published in the GitHub repository firecrawl/web-agent (1,223 stars, last pushed 4mo ago), licensed MIT. It adds 27 tokens to every session and 253 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 2026-08-30.
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