ma-deal-workbench-analysis

name

ma-deal-workbench-analysis

description

Produce a structured, judge-conforming JSON answer for an M&A deal-review task served by the deal workbench (draft-term issue registers, SPA closing/economics packages, committee escalation memos, carveout transition reviews, buyer deviation matrices). Use when a prompt asks you to act as buyer- or seller-side counsel for a specific project/deal_id and return only JSON matching a provided answer_template.json.

M&A Deal-Workbench Analysis

You are acting as transaction counsel (buyer- or seller-side, stated in the prompt) for one specific deal. The prompt names a deal_id (a string like PRJ_<NAME>) and an answer_template.json that defines the exact output shape, allowed enums, and stable IDs. Produce only a single JSON object conforming to that template — no narrative, no prose outside the JSON.

This skill is the transferable entry procedure. It does not contain any task-specific answers or final values; every value must be derived from the live workbench for the deal you are given.

0. Read the prompt and template first, before touching data

1. Read prompt.txt in full. Extract, verbatim:
   • your client side (buyer or seller),
   • the deal_id and project name,
   • the playbook_id or policy_id to compare against (named in the prompt or on the deal record),
   • the exact output requirement (which sections the package "must cover"),
   • the per-task unit/precision rules (they vary: "integer dollars", "percent points to two decimals", "percent points to one decimal", "holder percentages to four decimals", "months as integers", "dates as YYYY-MM-DD"). These override any default.
2. Read answer_template.json in full. It is the contract. Note:
   • required_top_level_fields / required_output_shape — must all be present,
   • allowed_enums — every enum field must take exactly a listed value (case-sensitive),
   • possible_issue_ids / stable_issue_ids / stable_redline_ids — issue and redline IDs are fixed vocabularies; never invent IDs, and use each stable ID at most once,
   • per-field type rules (integer or null, number or null, boolean or null, array).
3. Only one deal_id applies. Do not pull records from similarly-named projects.

1. Gather every workbench resource for the deal

Fetch the deal record and all linked sub-resources. The deal record (/api/deals/<deal_id>) carries a links map; fetch each one. A complete pass always includes:

• deal record (headline_value, upfront_cash, stock_value, milestone_value, client_side, client_name, counterparty_name, target_name, transaction_type, signing_date, meeting_date, playbook_id, policy_id, status)
• draft terms (/terms) — the current negotiated positions, each with term_id, category, numeric_value, unit, basis, clause_ref, staleness_flag
• playbook rules (/api/playbooks/<playbook_id>/rules) — seller PB_SELLER_A or buyer PB_BUYER_A; each rule has preferred_position, fallback_position, limit_value, limit_unit, risk_default
• policy thresholds (/api/policies/<policy_id>/thresholds) — when a policy_id is set; each threshold has category, threshold_value, threshold_unit, restricted_flag, approval_required
• consents, material-contracts, employees, cap-table, regulatory, diligence-findings, benchmarks, risk-estimates, notes, documents

The documented API list and the read-only SQL endpoint are described in the environment access file. Use the web API for per-deal resources; use SQL only for cross-table sanity checks. SQL takes a sql field (a single SELECT/WITH statement) plus the read-only token; PRAGMA and SHOW are rejected. Available tables: deals, draft_terms, playbook_rules, policy_thresholds, benchmarks, risk_estimates, cap_table, consents, employees, material_contracts, regulatory, diligence_findings, deal_notes, documents.

2. Establish the dollar basis for every percentage term

Each numeric draft term and each playbook/policy rule carries a basis. Convert percentages to dollars using the basis stated on that exact record — do not assume a single base for the whole deal:

• purchase price / equity value → use headline_value
• enterprise value → for an APA/merger where headline_value is the total consideration, use headline_value unless a record states a different figure
• upfront cash → use upfront_cash
• the term's own draft_value text sometimes states the dollar figure directly (e.g. "equal to 61.6 million dollars"); cross-check your computed amount against it

headline_value is the total deal value. For stock deals, headline_value = upfront_cash + stock_value + milestone_value (verify the identity holds; it does in this workbench). When a task says "calculate from headline purchase price", use headline_value.

All currency is integer USD (round half-up). Percent points and months are integers or decimals per the per-task precision rule. Never emit floats with trailing noise for dollars.

3. Classify each issue against the playbook / policy

For every stable issue ID the template offers, ask three questions:

1. Is there a current draft term? Match by category. If staleness_flag == "stale", the term is a distractor — exclude it unless the task explicitly wants stale terms. Stale + in-policy terms are excluded from escalation registers.
2. If present, does the draft exceed, fall below, or meet the playbook? Compare numeric_value to limit_value / preferred and fallback. Direction depends on which side benefits:
   • seller playbook wants caps/escrows/survival lower/shorter; a draft above the fallback is draft_exceeds_playbook.
   • buyer playbook wants caps/survival higher/longer and full scrape; a draft below the fallback is draft_below_playbook.
   • draft exactly at the fallback can be in_policy.
3. If absent, is the term required given the surrounding deal data? The prompt says: treat absent seller-protective (or buyer-protective) terms as missing_required_term where the surrounding deal data shows the term is needed — e.g. a carveout needs Section 1060 allocation and transfer-tax split; a stock deal with dispersed holders needs D&O tail and restrictive covenants; an SPA with a short survival fallback needs an escrow. Do not flag every missing template ID as an issue — only those the deal facts justify.

Map each issue's risk_rating from the playbook rule's risk_default (HIGH/MEDIUM/LOW) where one exists; otherwise infer from exposure magnitude. Map business_outcome to the allowed enum that best matches the term's economic effect.

recommended_action:

• add for missing_required_term,
• revise for draft_exceeds_playbook / draft_below_playbook / out_of_policy,
• accept for in_policy,
• escalate / approve_with_conditions / reject where the playbook required_action says to escalate or where committee policy is breached.

4. Compute deltas, shortfalls, and exposure

• delta_to_fallback_* = draft minus fallback in the direction of the deviation (signed so it represents the gap to close). For caps/escrows/survival where the draft is worse than fallback, this is draft − fallback (positive).
• shortfall_dollars / shortfall_to_fallback_usd / shortfall_to_preferred_usd = the dollar gap between the draft amount and the (fallback/preferred) amount, always a non-negative integer.
• required_fee_dollars / required_amount = fallback percent × basis.
• Per-issue exposure should cite the matching risk_estimate by estimate_id (RSK_PRJ_<DEAL>_0x): closing-certainty estimates pair with termination/financing/consent issues; indemnity-leakage estimates pair with cap/survival/scrape issues; transition-disruption estimates pair with TSA/carveout issues.
• quantified_impact_dollars ties an issue to a concrete source figure (a stranded-cost gap, PTO liability, consent amount-at-risk, or top-customer revenue).

5. Build the aggregate / summary block last

Aggregates are derived from the issue list and the source tables, not invented:

• counts (issue_count, high_risk_count, medium_risk_count, out_of_policy_issue_count, draft_below_playbook_count, missing_required_term_count, closing_blocker_count) = literal counts of the rows you produced.
• headline value = deal.headline_value.
• quantified exposure (low/high): the natural reading is the sum of the distinct risk estimates included in the package (e.g. closing-certainty + indemnity-leakage), not the same estimate re-added once per issue. State which components are included_exposure_components vs excluded_exposure_components.
• negotiation delta = the sum of the per-issue dollar deltas/shortfalls you computed.
• required-closing-consent amount at risk = sum of amount_at_risk over consents with required_for_closing == "yes".
• material-contract revenue requiring consent = sum of annual_revenue over material contracts with consent_required == "yes".
• employee totals = sum of count and sum of pto_liability across employee groups.
• priority order / negotiation priority = issue IDs ordered highest-leverage first (lead with the highest-risk, largest-dollar, or structurally blocking items; e.g. termination economics and financing/governing issues before employee/PTO items).

6. Closing readiness, blockers, and escalation routing

• A closing blocker is any required consent (required_for_closing == "yes"), any regulatory clearance (hsr_required == "yes" → regulatory_clearance blocker), and any material contract with consent_required == "yes" whose loss would be material. Tag blocker_type from the template enum and set must_be_satisfied_before_closing: true.
• Avoid double-counting: if one customer relationship appears as both a consent and a material contract, decide a single primary blocker representation and keep the IDs consistent across required_consent_ids / required_contract_ids and the blocker list.
• Closing readiness overall status: NOT_READY if any HIGH consent/regulatory blocker is unresolved; READY_WITH_CONDITIONS if only tradeable indemnity/escrow/survival gaps remain; READY only if no blockers and no out-of-policy terms.
• Committee escalation (policy-based tasks): escalate only terms that are (a) current (not stale), (b) restricted_flag == "yes" or exceeding a threshold_value, and (c) require M&A-Committee approval. Exclude stale, in-policy, or General-Counsel-only terms as distractors. excluded_in_policy_terms and excluded_in_policy_categories record what you intentionally left out and why.

7. Match the template exactly, then serialize cleanly

• Include every required top-level field and every field in each object — use null for "not applicable / not found", never omit a key the template lists.
• Every enum field takes a value from allowed_enums, exact casing. Stable IDs come only from the template's ID lists.
• Percent/month/count fields are typed per the template (integer or null vs number or null). Dollars are integers.
• Sort arrays the way the template's ordering instructions specify (e.g. transition_issues by issue_id ascending; priority_order by negotiation priority; required_redlines by redline_id).
• Serialize as strict JSON. Watch for set-literal typos in generated code ({a, b} is a Python set, not a dict — use {"k": v}). Validate json.loads before submitting.
• Return only the JSON object. No markdown fences, no commentary.

8. Verification checklist before finalizing

• deal_id, client_side match the prompt and deal record.
• Every required top-level field present; every template-listed object field present (null where N/A).
• Every enum value is in allowed_enums (case-sensitive).
• Every issue/redline/blocker ID is from the template's stable vocabulary.
• Dollar math reconciles: headline_value == upfront_cash + stock_value + milestone_value; each *_amount = percent × basis (integer).
• No double-counted blockers/consents; counts equal row counts.
• Distractor terms (stale, in-policy, wrong-approver) excluded, not invented.
• Output is a single JSON object, validated, no prose.

When to use the supporting references

• references/workbench_resources.md — the canonical list of deal sub-resources and what each contributes to an issue register / closing package.
• references/issue_classification.md — side-aware direction rules for draft_exceeds_playbook vs draft_below_playbook, and the "missing required term only when the facts justify it" rule, with the common issue→source mappings.
• references/aggregate_math.md — the deterministic formulas for the summary/aggregate fields and the exposure-component convention.