Borrowing it
Nothing to install: this file belongs to ashishwarkhade/Telegraph-MCP. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ashishwarkhade/Telegraph-MCP/main/.agents/skills/telegraph/SKILL.mdgit clone --depth 1 https://github.com/ashishwarkhade/Telegraph-MCPWrote 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/ashishwarkhade/telegraph-mcp/telegraph)<a href="https://agentmods.dev/skills/ashishwarkhade/telegraph-mcp/telegraph"><img src="https://agentmods.dev/badge/skills/ashishwarkhade/telegraph-mcp/telegraph/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/ashishwarkhade/telegraph-mcp/telegraph"><img src="https://agentmods.dev/badge/skills/ashishwarkhade/telegraph-mcp/telegraph.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00122 | $0.01890 |
| Opus 5 | $0.00061 | $0.00945 |
| Sonnet 5 | $0.00024 | $0.00378 |
| Haiku 4.5 | $0.00012 | $0.00189 |
Grade A, and why
telegraph 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 8d 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.
This is a copy
100% identical to telegraph — 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Telegraph Protocol
Telegraph is a permissionless marketplace for verifiable AI inference. Agents pay USDC per request. Miners — which can be Bittensor subnets, OpenAI, open-source models, or any AI API — compete to supply answers. A decentralized validator mesh grades responses using zkTLS-verified ground truth and WASM scoring scripts, reaches BFT consensus, and delivers a cryptographically finalized result.
The native token is MACHINA. Every USDC paid for inference flows through an open-market TWAP to buy MACHINA for the miner — demand for intelligence directly drives demand for the token.
MCP Tool Reference
Free tools (no payment)
| Tool | Purpose |
|---|---|
tg_node_list_subnets |
Full miner catalog — IDs, slugs, endpoints, input/output schemas |
tg_node_subnets_health |
Health status of all miner integrations |
tg_node_status |
Node identity, public key, chain info |
tg_engine_list_subnets |
Engine's view of available miners with capabilities and cost |
tg_daemon_categories |
Signal categories in the Daemon database (POLITICS, CLIMATE, TECHNOLOGY, …) |
tg_daemon_questions |
Query the Daemon's stored signals — filterable by category, source, time, interest |
tg_daemon_health |
Daemon health check |
The
subnetin some tool names is legacy — every provider is a miner today, whether a Bittensor subnet, a hosted model, or a private API.
Paid tools (x402 USDC per call)
| Tool | Purpose |
|---|---|
tg_engine_ask |
Auto-routed inference — Engine's LLM router selects the best miner for your query |
tg_engine_ask_subnet |
Direct inference to a specific miner by ID |
| Dynamic tools (auto-discovered) | Per-miner tools generated from the live integration registry (see below) |
Access Modes
1. Auto-routed inference (recommended)
The Engine classifies your natural language query into an Intent and routes to the highest-ranked miner for that task:
tg_engine_ask(query="7-day weather forecast for Dubai")
tg_engine_ask(query="Is this image AI-generated?")
tg_engine_ask(query="Summarize the latest clinical trial results for GLP-1 drugs")
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.
- 8d ago First seen · 152 lines · 122 tokens per session scan A 36fae463b7c1
telegraph is a skill published in the GitHub repository ashishwarkhade/Telegraph-MCP (0 stars, last pushed 13d ago), licensed MIT. It adds 122 tokens to every session and 1,890 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to telegraph, differing in 0 lines, and is treated as a copy.
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