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/firecrawl-workflows/firecrawl-deep-researchnpx skills add firecrawl/firecrawl-workflows --skill firecrawl-deep-researchgit clone --depth 1 https://github.com/firecrawl/firecrawl-workflowsWrote 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/firecrawl/firecrawl-workflows/firecrawl-deep-research)<a href="https://agentmods.dev/skills/firecrawl/firecrawl-workflows/firecrawl-deep-research"><img src="https://agentmods.dev/badge/skills/firecrawl/firecrawl-workflows/firecrawl-deep-research.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 5.1 | $0.00218 | $0.01274 |
| Opus 5 | $0.00109 | $0.00637 |
| Sonnet 5 | $0.00044 | $0.00255 |
| Haiku 4.5 | $0.00022 | $0.00127 |
Grade A, and why
firecrawl-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 5d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- firecrawl-deep-research — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Firecrawl Deep Research
Use this only for report-scale research: a rigorous, cited synthesis the user explicitly wants delivered as a formal written report. If the request is a product pick, a top-N list, a quick lookup, or anything answerable with a short search, stop; do not use this skill, let the request be handled the standard way.
This skill gathers its evidence from the open web. If the evidence base is the published literature — a literature review, or a biomedical, clinical, or other scientific topic where the answer lives in papers — use firecrawl-research-papers instead; it queries Firecrawl's paper index rather than searching websites.
Onboarding Interview
Infer the topic and output format from context. Before starting, unless already specified, always ask one short question to define the scope:
"How long do you want this research task to run?"
Map the answer to a depth tier in the Collection Plan below:
- A few minutes → Quick
- ~10-15 minutes → Thorough
- Longer / no limit → Exhaustive
If the topic itself is unclear, you may ask at most 1-2 additional concise questions (topic, or a critical angle/source constraint). Otherwise proceed once the runtime is set.
Firecrawl Collection Plan
Use Firecrawl search and scrape through the CLI or equivalent tool surface. Match depth to the runtime the user chose during onboarding.
- Quick (~a few minutes): search 3-5 queries and scrape 5-10 high-quality sources.
- Thorough (~10-15 minutes): search 5-10 queries from different angles and scrape 15-25 sources.
- Exhaustive (longer): search 10+ queries and scrape 25+ sources, including primary sources, research papers, expert views, and contrarian sources.
Avoid re-scraping URLs already returned with full content from a search-with-scrape result.
When Published Papers Are The Evidence
Search and scrape reach web pages. They do not query Firecrawl's research paper index, which holds paper abstracts with full text reachable per paper — largely biomedical and life-science literature from PubMed, bioRxiv, and medRxiv, plus arXiv preprints in CS, physics, and math.
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.
- 5d ago First seen · 145 lines · 218 tokens per session scan A dfd224ee3eed
firecrawl-deep-research is a skill published in the GitHub repository firecrawl/firecrawl-workflows (151 stars, last pushed 15d ago), licensed ISC. It adds 218 tokens to every session and 1,274 once invoked, about $0.0011 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…