crawling

crawling is a skill for Claude Code, Codex from omnigentx/jarvis. It costs 68 tokens per session (855 once invoked), scanned A, original, MIT.

A step-by-step method for finding the root cause of software bugs, slow performance, and failures in production systems. It covers reproducing the problem, forming likely explanations, testing them, and checking the fix.

In plain words
What is it for?
Use it to record reproduction steps, inspect errors and logs, compare possible causes, measure performance, investigate intermittent failures, write a test before fixing a bug, and verify the result.
Why use it?
It prevents random code changes that may hide the symptom while leaving the real problem in place.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to record reproduction steps, inspect errors and logs, compare possible causes, measure performance, investigate intermittent failures, write a test before fixing a bug, and verify the result.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/omnigentx/jarvis/crawling
Install

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.

Any agent
npx skills add omnigentx/jarvis --skill crawling
Clone the repo
git clone --depth 1 https://github.com/omnigentx/jarvis

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for crawling

README.md
[![agentmods](https://agentmods.dev/badge/skills/omnigentx/jarvis/crawling/github.svg)](https://agentmods.dev/skills/omnigentx/jarvis/crawling)
Your own site
<a href="https://agentmods.dev/skills/omnigentx/jarvis/crawling"><img src="https://agentmods.dev/badge/skills/omnigentx/jarvis/crawling/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.

agentmods 80×15 button for crawling

Your own site · 80×15
<a href="https://agentmods.dev/skills/omnigentx/jarvis/crawling"><img src="https://agentmods.dev/badge/skills/omnigentx/jarvis/crawling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 855 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00068 $0.00855
Opus 5.5 $0.00027 $0.00342
Sonnet 5.5 $0.00014 $0.00171
Haiku 4.5 $0.00007 $0.00085

Measured 1mo ago against content hash 7e2069d3b921, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

crawling 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 1mo 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.

backend/.fast-agent/skills/crawling/SKILL.md · 73 lines

How it starts

The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.

STORY CRAWLING WORKFLOW (recipe-based, AI-driven)

You analyse page STRUCTURE and emit a small RECIPE. The backend worker enumerates every chapter from that recipe and downloads them — the chapter list never passes through you, so this scales to 1000+ chapter stories without burning tokens.

Decision Tree

Add new story → has URL? use it : search_stories(query)
Check progress → get_crawl_status(job_id)
View library  → local_list_stories()

Step 0: GET A URL

  • User gave a URL → use it directly (skip search).
  • No URL → serpapi (Google search, fast) to find the story page. scrapling is for fetching a known URL, not searching. (Legacy web_search_stories is a slow per-site HTTP fallback — avoid unless serpapi is down.)

Step 1: DETECT STRUCTURE

detect_story_structure(url) renders the page (JS-aware) and returns, all LANGUAGE-AGNOSTIC:

  • link_patterns: same-domain links grouped by URL shape (digits→#) with counts + within_story_root flag + selector_hint. A high-count within-story pattern = the chapter links.
  • content_candidates: scored by paragraph density (pick narrative, not nav).
  • pagination_hints, story_root_guess.

Step 2: BUILD RECIPE (JSON)

  • LIST mode (page lists many chapters): {mode:"list", story_root:"/slug/", overview_url, chapter_url_pattern:"<sample chapter URL>", content_selector, title_selector, next_page_selector?}
  • CHAIN mode (single chapter page + a "next" link): {mode:"chain", story_root:"/slug/", first_chapter_url, next_chapter_selector, content_selector, title_selector}
  • story_root is REQUIRED in both — the same-story guard that blocks drift into recommended/other stories.
  • Find content_selector on a CHAPTER page (overview pages have no chapter body). Re-run detect_story_structure on a sample chapter URL if needed.

Step 3: VERIFY — MANDATORY (3 chapters)

verify_chapters(recipe_json) fetches the first 3 chapters and checks length, that chapters differ, and URL continuity.

  • ok=false → read issues, fix the recipe (usually content_selector), re-verify.
  • NEVER crawl an unverified recipe.

Read the full file on GitHub · 73 lines

Changes

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.

  1. 1mo ago First seen · 73 lines · 68 tokens per session scan A 7e2069d3b921

Subscribe to this mod's changes

crawling is a skill published in the GitHub repository omnigentx/jarvis (39 stars, last pushed 4d ago), licensed MIT. It adds 68 tokens to every session and 855 once invoked, about $0.0003 per session on Opus 5.5. 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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