convene

convene is a skill for Claude Code from FXDavid-OffbeatForex/tlc-hermes-skills. It costs 79 tokens per session (3,533 once invoked), scanned A, original, MIT.

A second-opinion tool for reviewing a financial market symbol with ten named trading methods, then combining their separate votes into one result: LONG, SHORT, or NOTRADE. It is analysis, not a guaranteed trading signal.

In plain words
What is it for?
Use it to review symbols such as BTCUSD, EURUSD, or AAPL at a chosen timeframe, with 1-hour analysis used by default. It helps compare trading opinions and produce a single summary verdict.
Why use it?
It gathers several trading viewpoints in one review instead of relying on a single method. The final combined verdict gives the analysis one consistent outcome.

Skill for Claude Code

Written for Claude Code: $ARGUMENTS substitution. Also seen: mentions AGENTS.md.

Good fit Use it to review symbols such as BTCUSD, EURUSD, or AAPL at a chosen timeframe, with 1-hour analysis used by default. It helps compare trading opinions and produce a single summary verdict.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/fxdavid-offbeatforex/tlc-hermes-skills/convene
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 FXDavid-OffbeatForex/tlc-hermes-skills --skill convene
Clone the repo
git clone --depth 1 https://github.com/FXDavid-OffbeatForex/tlc-hermes-skills

Made for: Claude Code.

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 convene

README.md
[![agentmods](https://agentmods.dev/badge/skills/fxdavid-offbeatforex/tlc-hermes-skills/convene/github.svg)](https://agentmods.dev/skills/fxdavid-offbeatforex/tlc-hermes-skills/convene)
Your own site
<a href="https://agentmods.dev/skills/fxdavid-offbeatforex/tlc-hermes-skills/convene"><img src="https://agentmods.dev/badge/skills/fxdavid-offbeatforex/tlc-hermes-skills/convene/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 convene

Your own site · 80×15
<a href="https://agentmods.dev/skills/fxdavid-offbeatforex/tlc-hermes-skills/convene"><img src="https://agentmods.dev/badge/skills/fxdavid-offbeatforex/tlc-hermes-skills/convene.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 79 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,533 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 $0.00079 $0.03533
Opus 5 $0.00039 $0.01767
Sonnet 5 $0.00016 $0.00707
Haiku 4.5 $0.00008 $0.00353

Measured 11d ago against content hash 555f26a09f9f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

convene 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 11d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/setup.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/convene/SKILL.md · 209 lines

How it starts

The opening of the file, as written. The whole thing — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Convene the Trading Legends Council on the symbol/timeframe/platform found in $ARGUMENTS (e.g. "convene BTCUSD 1h", "what does the council think of AAPL?", "convene the orderflow council on EURUSD"). Default timeframe is 1h if omitted.

0. Bootstrap (every run — cheap and idempotent)

Run scripts/setup.sh (in this skill's own directory) and capture its stdout as TLC_HOME (it clones/updates github.com/FXDavid-OffbeatForex/TLC under ~/.tlc/ and installs requirements.txt into an isolated venv at $TLC_HOME/.venv). cd "$TLC_HOME" and add the venv to PATH before every command below: export PATH="$TLC_HOME/.venv/bin:$TLC_HOME/.venv/Scripts:$PATH" (POSIX venvs use bin, Windows-native venvs use Scripts — only one will exist, so prepending both is safe everywhere). This makes plain python3 (or python on Windows, which usually has no python3 shim) resolve to the venv with deps installed — not to any other Python that happens to be on PATH (e.g. the harness's own bundled interpreter), which would silently run against the wrong environment and fail with confusing import errors. If the script fails, report the exact error — do not fall back to a half-installed run.

Do all of this skill's work in the terminal tool, inside $TLC_HOME — never execute_code or any other code-sandbox tool for tlc.* commands. Those sandboxes are a separate, isolated Python environment without this project's venv, MetaTrader5, or MBT's core module, so a tlc.* call there fails with a misleading ModuleNotFoundError/NotImplementedError. Three rules follow:

  • An import/ModuleNotFoundError is almost never a real data outage. It means the wrong tool ran the command, or the venv/cwd from §0 didn't carry into this call. Re-assert cd "$TLC_HOME" + the PATH export in terminal and retry there. Never let such an error override data you already fetched successfully earlier in the same conversation — reuse that data, don't discard it.
  • Read and write this skill's files in terminal too — temp frames.json/ packet.json/ballot.json, spec files, config.yaml/.env. Every path here is relative to $TLC_HOME; if you use any other tool for a file, give it the absolute path under $TLC_HOME, or the next terminal command won't find it.
  • The fetched OHLCV packet is your only market-data source. Never substitute a price or quote from web search, a browser, or any other tool — that is a subtler form of fabricating data.

Read the full file on GitHub · 209 lines

Files

What ships with it

1 file 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.

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. 11d ago First seen · 209 lines · 79 tokens per session scan A 555f26a09f9f

Subscribe to this mod's changes

convene is a skill published in the GitHub repository FXDavid-OffbeatForex/tlc-hermes-skills (5 stars, last pushed 2mo ago), licensed MIT. It adds 79 tokens to every session and 3,533 once invoked, about $0.0004 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 2026-08-31.