| name | signal-synthesizer |
| description | Combines per-agent DSE sub-scores (technical, fundamental, smart-money, sentiment, macro, volume-flow) into two synthesized signals — a long-term Investment signal and a short-term Momentum signal — each with a 1-10 DSE Composite Score, rating, confluence/conflict logic, and microstructure suppression. Use when the user wants to fuse multiple analyses into a final call, asks "what's the overall signal", "combine the agent scores", "should I invest or trade this", or needs the Mode Router / composite score for a Dhaka Stock Exchange ticker. |
| license | Apache-2.0 |
| compatibility | Prompt-first Agent Skill. Usable with the script absent. Script is Python 3.8+ stdlib-only, no network. |
| metadata | {"author":"stock-buddy","version":"0.2.0","prd_refs":["PRD-001:REQ-027","PRD-002:REQ-022"],"mode":["momentum","investment"]} |
Signal Synthesizer
Prompt-first skill. Fuse the agent scores by following the rules below.
scripts/synthesize.py is OPTIONAL — run it for exact weighting; the synthesis is valid
without it. Produce ONE card holding two signals (investment + momentum).
Role & objective
You are the Mode Router. Goal: blend per-agent sub-scores into a long-term Investment
signal and a short-term Momentum signal, each with a rating, confidence, a 1–10
Composite Score, and confluence/conflict governance.
When to use
"What's the overall signal?", "combine the agent scores", "should I invest or trade this?".
Run after the leaf skills; feed the chosen signal into risk-manager.
Inputs you need
agents — a map of {score −1..+1, confidence 0..1} for any of: technical,
fundamental, smart_money, sentiment, macro, volume_flow. Need at least technical
or fundamental. Optional microstructure. If volume_flow is absent, derive it as
0.8× technical (flag volume_flow_derived_from_technical).
Method (follow in order)
1. Weighted score per lens (renormalise weights over agents actually present):
- Investment: fundamental .40, smart_money .20, macro .15, sentiment .15, technical .10.
- Momentum: technical .45, volume_flow .20, smart_money .15, sentiment .12, fundamental .08 (veto-only).
2. Base rating from weighted w: ≥0.50 strong_buy · ≥0.15 buy · −0.15..0.15 hold ·
≤−0.15 sell.
3. Governance
- Strong conflict: any agent ≥0.50 AND any ≤−0.50 → stand_aside (don't average); −0.2 confidence.
- Confluence: if |w| ≥ 0.50, need ≥2 agents agreeing in sign at |score| ≥ 0.30; else
downgrade (strong_buy→buy, sell→hold) and −0.1 confidence.
- Momentum fundamental veto: if fundamental < −0.50 → momentum capped at stand_aside.
- Microstructure: circuit limit / floor / halt → momentum suppressed; investment keeps
thesis but defer execution.
4. Composite 1–10 = round(clamp(5.5 + 4.5·w, 1, 10)).
Confidence per lens = weight-blended agent confidence (after the governance penalties above).
Scoring rubric
Per lens: weighted score w (renormalised weights) → rating (≥0.50 strong_buy · ≥0.15 buy ·
−0.15..0.15 hold · ≤−0.15 sell), then apply governance (strong-conflict → stand_aside;
confluence shortfall → downgrade + −0.1 conf; momentum fundamental veto; microstructure
suppression). Composite 1–10 = round(clamp(5.5 + 4.5·w, 1, 10)). Report both Investment and
Momentum signals even when they disagree.
Output (emit this Thinking Card)
{ "skill": "signal-synthesizer", "ticker": "..", "as_of": "..",
"investment": { "score": 0.0, "composite_1_10": 5, "rating": "..", "confidence": 0.0,
"contributions": {}, "fair_value_note": "..", "thesis": "..", "exit_conditions": [], "reasoning": [] },
"momentum": { "score": 0.0, "composite_1_10": 5, "rating": "..", "confidence": 0.0,
"contributions": {}, "entry_trigger": "..", "stop_note": "..", "reasoning": [] },
"flags": ["..."], "disclaimer": "Educational analysis only. Not financial advice." }
DSE pitfalls
- Circuit/floor/halt suppress momentum entirely — technicals are unreliable without price discovery.
- A high average that lacks confluence is a false-confidence trap — downgrade it.
- Investment and momentum can legitimately disagree (e.g. cheap but no momentum) — report both honestly.
Optional precision helper
python3 scripts/synthesize.py --input data.json --pretty
Input shape: {"ticker":"..","agents":{"technical":{"score":..,"confidence":..}, ...}}.
Returns both signals with exact contributions and composite scores.
Worked example
agents technical +0.55/0.77, fundamental +0.44/0.62, smart_money +0.2, macro 0, sentiment +0.1
→ investment w ≈ +0.32 → buy, composite ≈ 7; momentum w ≈ +0.45, ≥2 agents agree → buy, composite ≈ 8.
References
Synthesis & governance detail: references/SYNTHESIS.md.
Output is educational analysis only, never financial advice.
