Investment Decision

clawock investment-decision

You are the model side of a clawock decision run. DeepSeek Harness owns conversation, memory and tools; clawock owns the decision contract. Your job is one file in, one file out: read a request, research, write a decision, let Python validate it. The model can never grade itself.

prepare ──► request.json ──► you: research + write decision.json ──► publish ──► receipt
(certified │                       (collect evidence,                │       (Python settles:
 context + │                        run the bull/bear debate,          │        evidence counts, debate
 gates)    │                        pick a bounded action)             │        links, money/FX to the cent)
           └───────────────────────────────────────────────────────────┘

Prerequisites

clawock must be installed (Python ≥ 3.11):

python -m pip install clawock

If a workspace is not initialized yet, create it with the workflow pinned — that flag is what turns decision.json into the enforced contract:

clawock init ./book --workflow investment-decision
clawock workflow install investment-decision --workspace ./book

The second command copies the readable contract (including references/decision-contract.md and the JSON Schema) into ./book/.agents/skills/investment-decision/ — a standard Agent Skill location that DeepSeek Harness also discovers.

The loop

1. Prepare

clawock run prepare --workspace ./book

Read the emitted request file (the request_file path printed on stdout, e.g. .clawock/work/<run_id>/request.json). It contains:

• task — the decision contract (evidence, opposing case, bounded action, reconciled amounts)
• context.documents — the certified context, per-file sha256 fingerprints (anything you cite must come from here or from your own research, and must be observed no later than as_of)
• workflow.parameters — gates: min_supporting_evidence, min_opposing_evidence, max_confidence_without_primary_source

2. Research, then debate, then decide

Research with the host's normal tools (web search, file reads, the live dashboard at https://kcnyu.github.io/clawock/ as source_class: market evidence). Collect both sides on purpose — the workflow has an opposing minimum, and publish refuses a decision whose bear case is a strawman:

1. Gather supporting evidence (filings/financials → primary, reputable secondary analysis → secondary, market data → market).
2. Actively seek the strongest counterargument you can find or construct — a genuine bear case, not a token objection. Record it as opposing evidence.
3. State the thesis and its invalidation conditions before choosing an action.
4. If the action proposes an order, compute both money identities from the context (quantity × unit price; × FX) — never invent prices, FX or sizes.

Write decision.json at the workspace root — artifact paths are resolved against the workspace root, not the request directory:

{
  "schema_version": 1,
  "workflow": {"id": "investment-decision", "version": "1.1.0"},
  "decision_id": "example-2026-08-08",
  "as_of": "2026-08-08T08:00:00+00:00",
  "subject": {"ticker": "EXAMPLE", "market": "US", "currency": "USD"},
  "evidence": [
    {"id": "filing-growth", "stance": "supporting",
     "summary": "The latest filed revenue figure grew year over year.",
     "source": "issuer filing", "source_class": "primary",
     "observed_at": "2026-08-08T07:30:00+00:00"},
    {"id": "valuation-risk", "stance": "opposing",
     "summary": "The current market multiple is above its stated range.",
     "source": "market data snapshot", "source_class": "market",
     "observed_at": "2026-08-08T07:45:00+00:00"}
  ],
  "debate": {
    "bull_case": {"summary": "Filed growth supports continued monitoring.",
                  "evidence_ids": ["filing-growth"]},
    "bear_case": {"summary": "Valuation leaves insufficient margin of safety.",
                  "evidence_ids": ["valuation-risk"]}
  },
  "thesis": {
    "statement": "Momentum is constructive, but price does not compensate for valuation risk.",
    "confidence": 0.7,
    "invalidation_conditions": ["Filed growth reverses"]
  },
  "decision": {
    "action": "watch",
    "rationale": "The opposing valuation evidence blocks an entry.",
    "evidence_ids": ["filing-growth", "valuation-risk"],
    "order": null
  }
}

Rules that are enforced by clawock run publish, not by this file:

1. debate.bull_case and debate.bear_case are both required and each cites evidence; the bear case must cite opposing-stance evidence — publish refuses without it. Python checks that linkage, not sincerity: make the bear case a genuine counterargument, never a strawman — that honesty is your contract.
2. Every evidence row needs a stance (supporting | opposing | context), a source_class (primary | secondary | market | agent) and an observed_at no later than as_of.
3. All evidence_ids references must exist (decision and both debate cases); conclusions in thesis.statement and decision.rationale should be backed by cited evidence.
4. If you propose an order, the currency amounts must reconcile to the cent; let the numbers come out of the context, never invent them.
5. Confidence above max_confidence_without_primary_source requires a cited primary source.

The sibling files next to this SKILL.md carry the full contract: references/decision-contract.md (with assets/order.example.json, an order-carrying decision whose two money identities reconcile). Introspect the exact artifact shape any time: clawock workflow schema investment-decision decision.json.

3. Publish and report

clawock run publish \
  --workspace ./book \
  --request ./book/.clawock/work/<run_id>/request.json \
  --artifact decision.json=./book/decision.json

Report the receipt's status and run_id, and if status is published, show the user a compact decision card:

Subject      EXAMPLE (US/USD)          decision_id example-2026-08-08
Bull         Filed growth supports continued monitoring.        [1 citing]
Bear         Valuation leaves insufficient margin of safety.    [1 citing]
Thesis       Momentum constructive, price does not compensate for risk.
Confidence   0.70  ·  Action watch  ·  Invalidation: filed growth reverses
Receipt      published  ·  run_id <run_id>  ·  certificate pinned

Never edit the receipt, never re-grade the decision, never "improve" the artifact after publish — Python settles.

Before publish: self-check

Run this checklist before invoking publish — Python re-checks all of it anyway, but a clean first pass beats a rejected receipt:

• both debate.bull_case and debate.bear_case present, each citing existing evidence_ids, the bear case citing opposing rows
• every cited evidence_id exists; no duplicates
• every evidence row has stance, source, source_class, and observed_at no later than as_of
• one primary row is cited whenever confidence exceeds the cap
• an order (if any) satisfies gross_amount_quote = quantity × unit_price and gross_amount_base = gross_amount_quote × fx_quote_to_base, to the cent

If publish rejects

The receipt lists validation_issues with code + message. Repair only the named issue and retry against the same prepared request; re-run prepare only if the context or workflow certificate changed.

Where things land

Learn from outcomes

After the stated horizon, record price/FX outcome evidence and run clawock workflow evaluate investment-decision --decision ... --outcome .... The result reconciles price and FX before assigning a basis-point score — it is evidence for the next decision, not portfolio P&L.

Record conversation verdicts

A conversation verdict (加仓/减仓/建仓/清仓/观望) is a decision — write it to the shared decision-mind ledger, the same memory/decisions.jsonl the daily OpenClaw brief writes to, so both sides can read it and the daily settlement round-trips it:

clawock record \
  --subject 00100 --market HK --currency HKD \
  --action reject --confidence 0.65 --driven-by fundamental \
  --bull "营收 +159% YoY,入通/海外霸榜催化" \
  --bear "净利率 -2368%,资不抵债,z+2.8σ 反转" \
  --thesis "高增长救不了资不抵债,先活下来" \
  --invalidation "站回 340" --invalidation "缩量企稳" \
  --emotion averaging_down --note "浮亏 -40% 的摊本冲动被压过,忍住没加"

--source defaults to conversation for DSH; other harnesses pass their own — OpenClaw --source openclaw, Claude Code --source claude, Codex --source codex. One ledger, one record command, every harness calls it; nobody edits decisions.jsonl directly.

Rules: the bear case and at least one observable invalidation condition are mandatory (the command rejects weak records); be honest about emotion pressure — fomo/revenge/averaging_down are the exact patterns this ledger exists to surface. Full schema (in the repository, not in the npm tarball): https://github.com/KCNyu/clawock/blob/master/docs/decision-mind-ledger.md

Learn more

Live proof on a real HK + US desk: https://kcnyu.github.io/clawock/ The same contract from other harnesses (OpenClaw skill, Claude Code instruction, Codex AGENTS.md, pure CLI): https://github.com/KCNyu/clawock/tree/master/examples/dsh/packages/clawock-dsh