tfl-fares

tfl-fares is a skill for Claude Code, Codex from oneill9/tfl-mcp-server. It costs 14 tokens per session (213 once invoked), scanned A, original, MIT.

A London transport fare lookup between two TfL stops. TfL is Transport for London; the results distinguish peak and off-peak prices and payment methods.

In plain words
What is it for?
Checking pay-as-you-go and cash single fares for journeys between named London stops, including peak-versus-off-peak comparisons.
Why use it?
It removes the need to search fare tables or resolve transport stop identifiers yourself.

Skill for Claude CodeCodex

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

Good fit Checking pay-as-you-go and cash single fares for journeys between named London stops, including peak-versus-off-peak comparisons.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/oneill9/tfl-mcp-server/tfl-fares
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 oneill9/tfl-mcp-server --skill tfl-fares
Clone the repo
git clone --depth 1 https://github.com/oneill9/tfl-mcp-server

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 tfl-fares

README.md
[![agentmods](https://agentmods.dev/badge/skills/oneill9/tfl-mcp-server/tfl-fares/github.svg)](https://agentmods.dev/skills/oneill9/tfl-mcp-server/tfl-fares)
Your own site
<a href="https://agentmods.dev/skills/oneill9/tfl-mcp-server/tfl-fares"><img src="https://agentmods.dev/badge/skills/oneill9/tfl-mcp-server/tfl-fares/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 tfl-fares

Your own site · 80×15
<a href="https://agentmods.dev/skills/oneill9/tfl-mcp-server/tfl-fares"><img src="https://agentmods.dev/badge/skills/oneill9/tfl-mcp-server/tfl-fares.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 213 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.
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 $0.00014 $0.00213
Opus 5.5 $0.00006 $0.00085
Sonnet 5.5 $0.00003 $0.00043
Haiku 4.5 $0.00001 $0.00021

Measured 2mo ago against content hash 07c6ffbeb8b8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

tfl-fares 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 2mo 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.

codex-plugin/skills/tfl-fares/SKILL.md · 26 lines

What it actually says

Use the fares MCP tool to look up fare information between two TfL stops.

When to use this skill

  • The user asks how much a tube/train journey costs
  • The user wants to compare peak vs off-peak fares
  • The user asks about pay-as-you-go vs cash prices

How to use

  1. Call the fares tool with fromName and toName parameters (stop names, not IDs)
  2. The tool automatically resolves stop names to NaPTAN IDs
  3. Results include pay-as-you-go and cash single prices for peak and off-peak travel
  4. Present fares clearly, distinguishing between peak and off-peak pricing

Example queries

  • "How much is the tube from Oxford Circus to Bond Street?"
  • "What's the fare from Bank to Canary Wharf?"
  • "How much does it cost to go from Paddington to Heathrow on the Elizabeth line?"
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. 2mo ago First seen · 26 lines · 14 tokens per session scan A 07c6ffbeb8b8

Subscribe to this mod's changes

tfl-fares is a skill published in the GitHub repository oneill9/tfl-mcp-server (1 stars, last pushed 3d ago), licensed MIT. It adds 14 tokens to every session and 213 once invoked, about $0.0001 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 2026-08-31.

Related

tfl-fares compared with skills from other repositories

tfl-fares next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
tfl-faresoneill9/tfl-mcp-serverSkill13d agoMITA14Claude Code, Codex
imagegenopenai/codexSkill133kyesterdayApache-2.0A113Codex
playwright-climicrosoft/playwrightSkill99kyesterdayApache-2.0A19Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79k4d agoMITA200Claude Code, Codex
systematic-debuggingobra/superpowersSkill313k3d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143ktodayMITA95Claude Code
next-partial-prefetching-adoptionvercel/next.jsSkill143ktodayMITA103Claude Code