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.
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The interactive on-ramp for this repository. It turns a user's goal into a concrete recommendation: which workflow to run, which skillset (skills-index category) it belongs to, the API requirement, and the setup path for Claude Web App or Claude Code.
A new user faces 74 skills + 12 workflows with no router. This skill is that
router. It is deterministic — a Python recommender (scripts/recommend.py)
consumes the repo metadata; this SKILL.md narrates the result conversationally.
Do not use this skill to execute trades, place orders, or auto-run other skills. It recommends and explains only.
From the user's message, extract:
Ask at most one brief clarifying question only if the goal is empty or has no discernible intent. Otherwise proceed — the recommender degrades gracefully.
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|advancedskills-index.yaml + workflows/*.yaml) automatically.assets/metadata_snapshot.json. The recommendation
is byte-identical in both environments — no behavior change for the user.Parse the JSON and explain, in the user's language:
display_name, cadence, ~estimated_minutes,
api_profile. State plainly what it does and when to run it.routing_diagnostics.status. For
ambiguous, name every candidate_personas entry and explain that the
ordered first match was selected. For fallback, state that no persona
matched and ask the user to rephrase; never present the beginner fallback as
an exact intent match.skillset.id (skills-index category).
manifest_status: active means a curated skillsets/<id>.yaml bundle ships
for this category (market-regime, core-portfolio, swing-opportunity,
trade-memory, strategy-research) — mention it as the install bundle for the
recommended workflow. manifest_status: deferred means no manifest yet
(e.g. honest-gap categories); the recommendation is workflow-based only.no_api_path: true → the entire recommended path
works without paid API keys (state this plainly); false → tell the user
which paid key(s) the path needs; null → honest gap, no path. (no_api is
the request flag — whether no-API mode was active — not whether the path is
free; always narrate no_api_path.) If a workflow was excluded under
--no-api, surface the rationale entry naming the paid integration (e.g.
"swing-opportunity-daily needs FMP").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.note when the research workflow
is recommended for a request containing backtest terms. It can evaluate
separately measured metrics but does not execute the backtest. Its
no_api_path does not describe the separate backtest tool or data.operational_roles entry for every
skill in the setup bundle or honest-gap suggestion. Explain standalone
rationale when present; keep enum values unchanged.rationale array and explain why this was recommended.Read references/setup_paths.md and walk the user through installing
setup_bundle — the recommender's deterministic install union over the
primary skillset and every secondary workflow (so nothing is dropped for a
multi-workflow recommendation). Enumerate setup_bundle.required →
recommended → optional, cite setup_bundle.sources to explain why each
skill is needed, and name skillset.manifest.related_workflows for how the
bundle is run. Narrate skillset.manifest (when present) as "what the
recommended skillset is". On an honest gap install suggested_skills. Do this
for whichever environment the user is in (Claude Web App .skill upload, or
Claude Code folder copy); call out any paid API keys those skills need.
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.
The JSON the recommender emits (stable, idempotent, sort_keys):
| Field | Meaning |
|---|---|
primary_workflow | Recommended workflow object, or null on an honest gap |
secondary_workflows | Supporting workflows (ordered, time-budget filtered) |
skillset | {id, source: skills-index.category, manifest_status, manifest}. manifest_status is active when skillsets/<id>.yaml ships, else deferred. manifest is the 5-key view {display_name, required_skills, recommended_skills, optional_skills, related_workflows} when active, else null. Describes the primary skillset only — not the install list |
setup_bundle | {required, recommended, optional, sources} — the actionable install union over the primary skillset and every secondary workflow (deterministic, tier-deduped). This is what to install. All-empty on an honest gap (use suggested_skills) |
suggested_skills | Skills to use when no workflow shipped (honest gap); else [] |
operational_roles | Skill id → {type, rationale?} for every setup-bundle skill, or every suggested_skills item on an honest gap |
no_api | Request-side: was no-API constraint mode active (flag or persona) |
no_api_path | Path-side: does the whole recommendation (primary + every secondary) work without paid API keys? true/false; null on an honest gap. This is the DoD's API-vs-no-API separation — narrate it explicitly |
honest_gap | true when no workflow exists for the intent |
note | Plain-language explanation for gaps / unmapped input |
rationale | Ordered list of why-this-was-recommended strings |
routing_diagnostics | {status, selected_persona, candidate_personas, explanation}. status is exact, ambiguous, or fallback; candidates are all pre-constraint persona matches in deterministic order |
setup_path_ref | Pointer to the setup-path reference |
scripts/recommend.py — the deterministic recommender (single source of
truth for routing).scripts/build_snapshot.py — regenerates assets/metadata_snapshot.json
from the SSoT; --check guards drift (pre-commit + CI).scripts/intent_benchmark.py — validates the fail-closed bilingual routing
corpus, persona shadowing contracts, and metamorphic invariants.references/intent_routing.md — the persona table, the 10-question contract,
the --no-api credential rule, and scoring tie-breaks.references/setup_paths.md — Claude Web App vs Claude Code setup steps.assets/metadata_snapshot.json — generated SSoT digest for the Web App
fallback. Never edit by hand; run build_snapshot.py.assets/intent_benchmark_v1.json — 211 explicitly labeled EN/JA routing
cases with 1.0 precision/recall and per-persona/workflow coverage gates.eab8d5c
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