tvchart

A coding-agent guide for controlling a live TradingView Lightweight Charts widget, a web chart used to display financial price data.

In plain words
What is it for?
Use it to inspect or update a chart's symbol, time interval, indicators, markers, price lines, layout and other saved state.
Why use it?
It gives the agent a defined way to read the chart's current state and change its displayed market data and layout.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/deeleeramone/pywry/tvchart
Any agent
npx skills add deeleeramone/PyWry --skill tvchart
Clone the repo
git clone --depth 1 https://github.com/deeleeramone/PyWry

Made for: Claude Code, Codex.

Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,188 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00033 $0.02188
Opus 5 $0.00016 $0.01094
Sonnet 5 $0.00007 $0.00438
Haiku 4.5 $0.00003 $0.00219

Measured 2d ago against content hash e77e4703fe95, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

tvchart 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 2d 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.

pywry/pywry/mcp/skills/tvchart/SKILL.md · 245 lines

How it starts

The opening of the file, as written. The whole thing — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.

TradingView Chart — Agent Reference

Use this when an agent needs to read or mutate a live tvchart widget. Every action is an MCP tool call on the PyWry FastMCP server — there are no local helpers, no side channels, no custom tools. Pick the typed tool that matches the user's intent, pass the required arguments, and quote the tool's return values in your reply.

Every tool takes widget_id

widget_id identifies which chart to operate on. On a single-chart server the framework auto-resolves it from the registry; on a multi-chart server you must pass it explicitly. Read the value from the user's @<name> attachment (the chat prepends --- Attached: <name> ---\nwidget_id: <id>) or call list_widgets() to enumerate.

Reading chart state — always via tvchart_request_state

Never report symbol / interval / indicators / bars / last close from memory. Call the tool, quote the return.

tvchart_request_state(widget_id)
  → {
      "widget_id": "chart",
      "state": {
        "symbol": "AAPL",
        "interval": "1D",
        "series": [{ "seriesId": "main", "bars": [...], ... }],
        "indicators": [...],
        "visibleRange": { "from": ..., "to": ... },
        "chartType": "Candles",
        ...
      }
    }

When the user asks "what's on the chart", "what's the current price", "what indicators are applied", call this and quote from state.

Mutating tools — all confirm the change

Every mutation returns the real post-change state. The model never has to guess whether the change took effect. If the mutation didn't land within the settle window, the tool includes a note field — relay it to the user.

Symbol change

tvchart_symbol_search(widget_id, query, auto_select=True,
                      symbol_type=None, exchange=None)
  → { "widget_id": "chart", "symbol": "MSFT", "state": {...} }

Use this to switch the ticker. auto_select=True commits the selection; auto_select=False just opens the search dialog for the user. The tool polls chart state until the symbol actually changes to the target (up to ~6s) so the return reflects reality.

Read the full file on GitHub · 245 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. 2d ago First seen · 245 lines · 33 tokens per session scan A e77e4703fe95

Subscribe to this mod's changes

tvchart is a skill published in the GitHub repository deeleeramone/PyWry (93 stars, last pushed 8d ago), licensed Apache-2.0. It adds 33 tokens to every session and 2,188 once invoked, about $0.0002 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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