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 glebis/claude-skills --skill firecrawl-researchgit clone --depth 1 https://github.com/glebis/claude-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/glebis/claude-skills/firecrawl-research)<a href="https://agentmods.dev/skills/glebis/claude-skills/firecrawl-research"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/firecrawl-research/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/glebis/claude-skills/firecrawl-research"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/firecrawl-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 88 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00079 | $0.02092 |
| Opus 5 | $0.00039 | $0.01046 |
| Sonnet 5 | $0.00016 | $0.00418 |
| Haiku 4.5 | $0.00008 | $0.00209 |
Grade A, and why
firecrawl-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 11d 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 — 319 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FireCrawl Research
Overview
Enrich research documents by automatically searching and scraping web sources using the FireCrawl API. Extract research topics from markdown files and generate comprehensive research documents with source material.
When to Use This Skill
Use this skill when the user:
- Says "Research this topic using FireCrawl"
- Requests to enrich notes or documents with web sources
- Wants to gather information about topics listed in a markdown file
- Needs to search and scrape multiple topics systematically
How It Works
1. Topic Extraction
The script automatically extracts research topics from markdown files using two methods:
Method 1: Headers
## Spatial Reasoning in AI
### Computer Vision Applications
Both Spatial Reasoning in AI and Computer Vision Applications become research topics.
Method 2: Research Tags
- [research] Large Language Models for robotics
- [search] Theory of Mind in autonomous driving
Both tagged items become research topics.
2. Search and Scrape
For each topic:
- Searches FireCrawl with the topic as query
- Retrieves up to N results (default: 5)
- Automatically scrapes full content from each result
- Extracts markdown-formatted content (main content only)
3. Output Generation
Creates new markdown files in the specified output directory:
- One file per topic
- Filename:
{topic}_{timestamp}.md - Contains: title, date, sources count, full scraped content
- Each source includes: title, URL, markdown content
Usage
Basic Usage
python scripts/firecrawl_research.py research.md
Outputs to current directory.
Specify Output Directory
python scripts/firecrawl_research.py research.md ./output
Creates files in ./output/ folder.
Limit Results Per Topic
python scripts/firecrawl_research.py research.md ./output 3
Retrieves maximum 3 results per topic.
Configuration
API Key Setup
- Copy
.env.exampleto.env:cp .env.example .env
What ships with it
9 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.
- .claude-plugin/plugin.json 300 B
- .env.example 66 B
- assets/references.bib 1.8 KB
- assets/templates/myst-scientific-paper.md 3.0 KB
- assets/templates/pandoc-scholarly-paper.md 2.3 KB
- requirements.txt 660 B
- scripts/convert_academic.py 4.0 KB runs code
- scripts/firecrawl_research.py 5.6 KB runs code
- scripts/generate_bibliography.py 4.4 KB runs code
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.
- 11d ago First seen · 319 lines · 79 tokens per session scan A f5afba45e96c
firecrawl-research is a skill published in the GitHub repository glebis/claude-skills (374 stars, last pushed 8d ago), licensed MIT. It adds 79 tokens to every session and 2,092 once invoked, about $0.0004 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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