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/indreamer/telegram-codex-bridge/web-markdown-fetchnpx skills add InDreamer/telegram-codex-bridge --skill web-markdown-fetchgit clone --depth 1 https://github.com/InDreamer/telegram-codex-bridgeWrote 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/indreamer/telegram-codex-bridge/web-markdown-fetch)<a href="https://agentmods.dev/skills/indreamer/telegram-codex-bridge/web-markdown-fetch"><img src="https://agentmods.dev/badge/skills/indreamer/telegram-codex-bridge/web-markdown-fetch.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 | $0.00096 | $0.01151 |
| Opus 5 | $0.00048 | $0.00575 |
| Sonnet 5 | $0.00019 | $0.00230 |
| Haiku 4.5 | $0.00010 | $0.00115 |
Grade A, and why
web-markdown-fetch scanned grade A with 1 finding 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 4d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -L "https://markdown.new/https://example.com" This is a copy
100% identical to web-markdown-fetch — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Web Markdown Fetch
Core Rule
When reading any target URL, apply these methods in strict order:
https://markdown.new/<full-url>https://defuddle.md/<full-url>https://r.jina.ai/<full-url>- Scrapling fallback (
scrapling extract ...)
Do not jump to Scrapling before trying the three mirror prefixes. For successful mirrors, keep evaluating in-order and select the best complete candidate; do not stop at the first partial success.
Treat asset handling as mandatory:
- Persist fetched markdown and discovered images under a per-session agent asset directory.
- Keep image assets enabled by default;
--no-save-assetsis allowed only if the user explicitly requests disabling image persistence. - For image-analysis requests in pi, use
readon the downloaded local image files first before any external vision fallback.
Pi Adaptation
This skill is adapted for pi package loading.
- When this repo is loaded as a pi package, the skill can be invoked as
/skill:web-markdown-fetch <url>. - Do not assume Codex-only session variables or Codex-only directories.
- The bundled helper auto-detects Pi/Codex/generic session ids when available, then falls back to a workspace-derived session id.
- Saved image files are meant to be opened locally with pi's
readtool.
Workflow
- Normalize the input URL. If the scheme is missing, prepend
https://. - Try
markdown.newfirst. - If the output is empty, blocked, timed out, or clearly wrong, try
defuddle.md. - If that still fails, try
r.jina.ai. - For usable mirror outputs, score all candidates and pick the most complete one.
- If all three fail, run Scrapling CLI fallback.
- Save fetched markdown and discovered markdown-image assets to a temp directory keyed by the current agent session when detectable; otherwise use the workspace-derived fallback id.
- Explicitly report the resolved asset directory path and the image save count (
images_saved/images_discovered). - If the user asks for visual details such as a diagram, chart, or screenshot, inspect saved local image files first with
read. - Do not call external vision services first for image interpretation; only use them as fallback when local image reading is unavailable or explicitly requested by the user.
- After each successful fetch, report a completeness score (
0-100) and whether it is full (is_full=true/false). - Return the extracted content and explicitly state which method succeeded.
- If Scrapling reports SSL certificate verification errors, retry Scrapling with
--no-verify.
What ships with it
3 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.
- 4d ago First seen · 113 lines · 96 tokens per session scan A fda2974b9278
web-markdown-fetch is a skill published in the GitHub repository InDreamer/telegram-codex-bridge (26 stars, last pushed 3mo ago), licensed MIT. It adds 96 tokens to every session and 1,151 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to web-markdown-fetch, differing in 0 lines, and is treated as a copy.
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