| name | cashflow-forecast-worksheet |
| description | Family office: Produce a 12-month rolling cashflow forecast. Captures inflows, outflows, timing, and cushion requirements. |
Family Office · Cashflow Forecast Worksheet
For Claude: How to Use This Skill
Skill instructions are preloaded in context when this skill is active. Do not
perform filesystem searches or tool-driven exploration to rediscover them; use
the guidance below directly.
When to Use
Invoke when the advisor asks about:
- cashflow forecast
- cash management
- 12-month cash plan
- rolling cashflow
Customer Pain (VOC)
Synthesized from family-office operator interviews (see references/voc-evidence.md for full provenance):
- Founders facing a 12-18 month liquidity event need pre/during/post cash planning — [4T0BpwFhRvo @ 00:30]
- Pre-liquidity-event founders need a different cash posture than post-liquidity wealth — [4T0BpwFhRvo @ 10:27]
- Investment universes for waiting-on-liquidity founders differ from typical wealthy clients — [4T0BpwFhRvo @ 10:45]
- Estate teams often miss the principal's actual short-term liquidity needs — [HV86G3RCPV0 @ 20:24]
- Operators want better liquidity forecasting across many subscription agreements — [dLoQJfqGgag @ 29:14]
Artifact Specification
This skill produces a single named deliverable:
- Artifact:
Cashflow Forecast Worksheet
- Format at this iteration: markdown (
artifact.md) plus a structured
interview.json capturing every advisor input. PDF / DOCX / XLSX companion
renders and DMS / Snowflake push land in the execution-pipeline PR tracked
under issue #427.
The artifact is written to a skill-local path, not a global directory:
<invocation-cwd>/artifacts/family-office/cashflow-forecast-worksheet/<YYYYMMDD-HHMMSS>/
artifact.md
interview.json
manifest.json
Interview Inputs
Minimum-viable interview — the skill asks only what is needed to personalize
the deliverable. Pre-fill rules against family memory land in the execution-
pipeline PR.
forecast_start_month — Forecast start month (YYYY-MM)?
recurring_inflows — Recurring inflows (source, amount, cadence)?
recurring_outflows — Recurring outflows (category, amount, cadence)?
lumpy_known_items — Known lumpy inflows/outflows and timing?
minimum_cushion — Minimum liquidity cushion?
Workflow
- Run
python scripts/agent.py --config config.json (or invoke via Claude
Code with a config blob).
- The agent validates config, runs the interview (TTY or fixture-driven),
and produces the artifact under the canonical local path.
- The agent writes
manifest.json with artifact metadata (name, version,
content hash, pillar, skill_name, created_at).
- The agent optionally writes memory entries to the knowledge skill's
memory_objects table via psycopg if config.memory_dsn is provided.
Without a DSN, memory writes are skipped cleanly.
Memory Conventions
Memories written by this skill are tagged with:
subject = the artifact name
source = "cashflow-forecast-worksheet"
memory_type ∈ {decision, assumption, commitment, open_question}
Security & Confidentiality
- Never log interview answers or artifact contents at INFO level.
- Never include SSN, EIN, account numbers, or full financial amounts in
log lines. If a WHERE-clause field carries such data, log only a sha256
hash.
- The artifact directory is local-only at this iteration. DMS push (with
confidentiality-label routing) is handled by the execution-pipeline PR.
Reference