Trading Skills Navigator

Recommend the right trading workflow, skillset, API profile, and setup path from a natural-language goal. Use this as the on-ramp when a user expresses a trading or investing goal and needs to know which skill/workflow to use, where to start, or whether something works without paid API keys — e.g. “where do I start”, “which skill should I use”, “I want to swing trade only when the market is favorable”, “what works without API keys”, “どれを使えばいい”, “API キー無しで 使えるものは”. Routes and explains only; it never executes trades or auto-runs other skills, and it is honest when no workflow has shipped yet.

No API

View Source on GitHub

Table of Contents

1. Overview

Trading Skills Navigator

2. When to Use

  • The user expresses a trading/investing goal and asks where to start or which skill/workflow to use (“どれを使えばいい”, “where do I start”).
  • The user asks what works without paid API keys.
  • The user wants the no-API vs API path separated, or a beginner path.
  • The user describes a persona (“part-time swing trader”, “dividend investor”, “I want to short”, “I want to backtest ideas”) and needs routing.

Do not use this skill to execute trades, place orders, or auto-run other skills. It recommends and explains only.

3. Prerequisites

  • Reads local skills-index.yaml + workflows/*.yaml (or bundled snapshot); no network
  • Python 3.9+ recommended

4. Quick Start 

python3 skills/trading-skills-navigator/scripts/recommend.py \
  --query "<the user's goal, verbatim>" \
  --format json
  # optional: --no-api  --time-budget 15m|30m|60m|90m|any
  #           --experience beginner|intermediate|advanced

5. Workflow

Step 1 — Capture the goal and constraints

From the user’s message, extract:

  • The natural-language goal (verbatim is fine).
  • Optional constraints: no-API only? a daily time budget (15m/30m/60m/90m)? experience level (beginner/intermediate/advanced)?

Ask at most one brief clarifying question only if the goal is empty or has no discernible intent. Otherwise proceed — the recommender degrades gracefully.

Step 2 — Run the recommender 

python3 skills/trading-skills-navigator/scripts/recommend.py \
  --query "<the user's goal, verbatim>" \
  --format json
  # optional: --no-api  --time-budget 15m|30m|60m|90m|any
  #           --experience beginner|intermediate|advanced
  • In Claude Code the script reads the repo-root SSoT (skills-index.yaml + workflows/*.yaml) automatically.
  • In the Claude Web App there is no repo root; the script transparently falls back to the bundled assets/metadata_snapshot.json. The recommendation is byte-identical in both environments — no behavior change for the user.

Step 3 — Narrate the result conversationally

Parse the JSON and explain, in the user’s language:

  • Primary workflow — display_name, cadence, ~estimated_minutes, api_profile. State plainly what it does and when to run it.
  • Secondary workflows — if any, how they relate (e.g. “run the regime check first, then this when it allows risk”).
  • Skillset — the skillset.id (skills-index category). Note manifest_status: deferred means a bundled skillset manifest is a later phase; today the recommendation is workflow-based.
  • No-API vs API — if no_api is true, say it works without paid keys. If a workflow was excluded under --no-api, surface the rationale entry that explains which paid integration caused it (e.g. “swing-opportunity-daily needs FMP”).
  • Honest gap — if honest_gap is true there is no shipped workflow for this intent. Say so directly, then present suggested_skills from the relevant category and relay the note. Never invent a workflow.
  • Always read the rationale array and explain why this was recommended.

Step 4 — Explain the setup path

Read references/setup_paths.md and walk the user through the path for their recommended workflow’s skills specifically (the actual required_skills / optional_skills from the JSON), for whichever environment they use (Claude Web App .skill upload, or Claude Code folder copy). Call out any paid API keys those skills need.

Step 5 — Point to the learning loop

Close by pointing the user at trader-memory-core and the trade-memory-loop / monthly-performance-review workflows so every recommended path feeds the Plan → Trade → Record → Review → Improve loop.

6. Resources

References:

  • skills/trading-skills-navigator/references/intent_routing.md
  • skills/trading-skills-navigator/references/setup_paths.md

Scripts:

  • skills/trading-skills-navigator/scripts/build_snapshot.py
  • skills/trading-skills-navigator/scripts/recommend.py