version: "1.0.0" name: tres-rollup-rules description: > Analyze an organization's sub-transaction patterns in TRES Finance, identify groups of repetitive transactions, and propose data-driven rollup rules that consolidate them into one aggregated entry per interval (daily or monthly) for cleaner ERP integration. Also lists and deletes rollup rules. Trigger this skill whenever the user asks about rollup rules, transaction aggregation, consolidating transactions, reducing transaction noise, rolling up gas fees, rolling up staking rewards, rolling up micro-transactions, or collapsing many small ledger entries into fewer summary entries. Also trigger on "create a rollup rule", "suggest rollup rules", "what should I roll up", "show my rollup rules", "delete a rollup rule", "aggregate transactions", "too many transactions", "reduce transaction count", "roll up fees", "daily rollup", "monthly rollup". If a wallet has too many transactions, high-frequency activity, or noisy ledger entries, proactively suggest rollup rules. For computing the EXACT impact of a single already-specified rule or reviewing submitted/pending rules, use the tres-rollup-review skill instead. compatibility: "Requires TRES Finance MCP connector"

TRES Finance — Rollup Rules

Analyze an organization's sub-transaction patterns, identify groups of repetitive transactions, and propose rollup rules that consolidate them into a single entry per interval for cleaner ERP integration. This is a data-driven discovery flow — you find the candidates from the data, validate each against real transactions, then present and create them.

A rollup rule is keyed on FOUR dimensions that together define exactly which sub-transactions it claims: internalAccount (wallet) + asset KEY + platform + balanceFactor (direction). Optional discriminating filters (fees, methodIds, subtxType, amount bounds, counterparties) narrow it further. Everything you discover and propose must map onto this shape — see the Rule Field Reference at the bottom.

A rollup is non-destructive: the original raw sub-transactions are always preserved and visible in the Rollup Breakdown report.

All GraphQL runs through the TRES Finance MCP connector (execute tool; validate with validate_query first when unsure). All variable keys and nested input fields MUST use camelCase (e.g. internalAccountId, balanceFactor), NEVER snake_case.

Routing

• "Suggest / create / propose rollup rules", "too many transactions", **"roll up

X"** → run the full discovery pipeline (Steps 0–6 below). This is the main flow.

• "Show / list my rollup rules" → Section A (List existing rules), then stop.
• "Delete a rollup rule" → Section C (Delete rules).
• "Review this specific rule" / "what would this rule match" → hand off to the

tres-rollup-review skill.

Step 0 — Confirm Scope

Establish scope with the user, but keep it light — only the analysis is scoped, the rules themselves are usually open-ended.

Analysis window (OPTIONAL)

A period only narrows the discovery queries so you look at recent, representative activity. It is NOT required, and it is NOT the rule's date range.

• "Q1 2025" → start: 2025-01-01T00:00:00Z, end: 2025-03-31T23:59:59Z
• "last 3 months" → compute from today

If the user gives no period, analyze all history — that is fine and common.

Rule date range (PREFER OPEN-ENDED)

The rules you create should normally have no start/end date — they default to "from the beginning of time, indefinitely" so they keep catching matching transactions going forward. Only set startDate/endDate when the user explicitly wants the rule bounded.

Wallets (optional, default: all)

The user may scope to specific wallets.

Asset classes (optional, default: all non-spam)

The user may scope to specific asset classes (e.g. "just stablecoins", "ETH"). Remember: a class (e.g. USDC) can span many asset keys/chains, but each rule targets ONE key — see the asset-class bridge in Step 2.

Clustering guidance (optional)

Hints like "focus on gas fees", "ignore staking rewards under $10", "group ETH transfers by methodId".

Confirm scope briefly, then start:

"I'll look for rollup candidates across all wallets and all assets (analyzing

all history). Rules I propose will be open-ended unless you want them date-bounded.

Starting now."

Step 1 — Inventory

Run these (in parallel where possible).

1a. Wallets

query Wallets { internalAccount { totalCount results { id name identifier parentPlatform platforms balancesCount status } } }

Collect wallet id (integer) — this is the rule's internalAccountId. Use platforms (plural list) and parentPlatform (string); there is no singular platform field on wallets.

1b. Existing rollup rules (so you don't duplicate coverage)

query ExistingRules { subTransactionRollupRule { totalCount results { id name interval status startDate endDate createdBy lastSuccessfulRunAt rule } } }

rule is the JSON config (internal_account_id, asset_id, platform, balance_factor, fees, …). Note which (account, assetKey, direction) tuples are already covered by Active or Pending rules — skip those. Ignore Disabled rules (they are superseded versions, not live coverage). Also study the existing rule names here to learn the org's naming convention (see Naming below).

1c. Total sub-transactions in scope

query InScope($ts_Gte: DateTime, $ts_Lte: DateTime) {
  subTransaction(timestamp_Gte: $ts_Gte, timestamp_Lte: $ts_Lte) { totalCount }
}

(Omit the timestamp args entirely when analyzing all history.)

Report: "Found X wallets, Y existing rules (Z active), N sub-transactions in scope."

Step 2 — Discovery (the core analysis)

Use aggregation queries to find which (wallet, asset, direction) groups have the most repetitive volume, then drill into discriminating filters.

Filter-name reference (verified — use these EXACT names)

• Wallet: belongsTo_In: [ID] (array, even for one id)
• Asset by key: asset_In: [ID] (array of asset KEYS, e.g. ["ethereum_native"])
• Asset class: asset_AssetClass_In: [ID]
• Direction: balanceFactor: Float (-1 = OUTFLOW, 1 = INFLOW)
• Amount: amount_Gte / amount_Lte; fiat: fiatValue_Gte / fiatValue_Lte
• Counterparty: sender_Identifier_In: [String], recipient_Identifier_In: [String]
• Method: tx_MethodId: String (single) or group by tx__method_id
• Sub-tx type: type: String / type_In: [String] (FinancialAction) — filter with the

lowercase value ("gas", "reward", …); note this is the opposite casing from the mutation's UPPERCASE subtxType enum. groupBy: ["type"] works too.

• Dates: timestamp_Gte / timestamp_Lte
• Exclude already-rolled-up sub-txs: excludeRollups: true
• Exclude gas/fee sub-txs: excludeGasFees: true; exclude spam: excludeSpam: true
• Internal transfers only: internalTransfer: true

Always exclude already-rolled-up sub-txs

Add excludeRollups: true to every discovery/count query. It drops ROLLUP / ROLLUP_FEE sub-txs so your counts reflect what a new rule would actually capture — matching the rollup engine's own selection. Without it, groups a prior rule already rolled up would be double-counted. (onlyRollup: false does NOT do this — it's a no-op.) To inspect what an existing rule produced, query type_In: ["rollup", "rollup_fee"], typeId: "<rule_id>" — typeId only means the rollup rule id when paired with a rollup type.

2a. Group by the rule's real key (wallet id + asset key + platform + direction)

query GroupByKey($ts_Gte: DateTime, $ts_Lte: DateTime) {
  subTransaction(
    timestamp_Gte: $ts_Gte, timestamp_Lte: $ts_Lte,
    excludeRollups: true,
    groupBy: ["belongs_to", "asset", "platform", "balance_factor"],
    aggregations: [
      { field: id, function: COUNT, alias: "count" },
      { field: fiatValue, function: AVG, alias: "avgFiat" }
    ]
  ) {
    groupedAggregations { groupKey results { alias value } }
  }
}

groupKey gives you the wallet id (→ internalAccountId), the asset key (→ assetId), platform, and balanceFactor — exactly the four fields a rule needs, no name/symbol guessing. Groups under ~50 sub-txs are rarely worth a rule.

The asset-class bridge

Users think in asset classes ("roll up all our USDC"); a rule targets one asset key. When the user scopes by class, you may first group by asset__asset_class__symbol to prioritize, but you must then expand each promising class into its concrete asset keys (Step 2a already returns keys) and propose one rule per (wallet, assetKey, platform, direction). In the report, surface the sibling keys on the same wallet so the user sees which variants each rule does and does not cover.

2b. Drill down by methodId (per significant group)

query DrillMethod($ts_Gte: DateTime, $ts_Lte: DateTime, $belongsTo_In: [ID], $asset_In: [ID], $balanceFactor: Float) {
  subTransaction(
    timestamp_Gte: $ts_Gte, timestamp_Lte: $ts_Lte,
    belongsTo_In: $belongsTo_In, asset_In: $asset_In, balanceFactor: $balanceFactor,
    excludeRollups: true,
    groupBy: ["tx__method_id"],
    aggregations: [
      { field: id, function: COUNT, alias: "count" },
      { field: amount, function: AVG, alias: "avgAmount" },
      { field: amount, function: MAX, alias: "maxAmount" }
    ]
  ) {
    groupedAggregations { groupKey results { alias value } }
  }
}

2c. Drill down by sub-tx type (optional)

Repeat the same query shape with groupBy: ["type"] to see whether a specific sub-tx type dominates the group — useful only if you intend a subtxType rule.

Analysis strategy

Reason about which combinations make the best rules:

1. Coverage — each rule should claim a meaningful share of its group.
2. Discriminating filter (when useful, not required) — the four key fields (wallet +

assetKey + platform + direction) plus fees fully define most rules. Add an optional narrowing filter (methodIds, amount bounds, counterparty, or subtxType) only when it sharpens a heterogeneous group — many good rules use none. subtxType in particular is optional; don't add it reflexively.

1. Interval — DAY for high-frequency groups (>~500 sub-txs), MONTH otherwise.
2. Existing rules — skip (account, assetKey, direction) tuples already covered by an

Active/Pending rule. Never judge an existing rule by its current match count alone: a rule that has been running has already rolled up its pool, so the live (non-rollup) sub-txs that remain are just the recent unprocessed few — a hard-working rule looks idle. To see what it actually did, count the rollups it produced: subTransaction(type_In: ["rollup","rollup_fee"], typeId: "<rule_id>"). Only treat a rule as ineffective if it has produced ~nothing and matches ~nothing now.

1. Overlap (soft) — two rules on the same wallet + assetKey + platform + direction with

non-disjoint filters can claim the same sub-txs. This is not fatal: the engine processes rules deterministically by id (PK), so a shared sub-tx is always claimed by the same rule. Prefer non-overlapping rules, but overlap is a note, not a blocker.

For each candidate, note WHY this combination was chosen.

Step 2.5 — Validate candidates (MANDATORY quality gate)

At this point you hold your N candidate rule objects (from Step 2) in context. Invoke the `tres-rollup-review` skill (via the Skill tool) once — this loads the review checks into your own context (it is not a separate agent and takes no arguments; the candidates are already here, nothing is passed). Then, following those instructions, walk your candidates one at a time — for each candidate run the review's Check 1 (one subTransactionRollupRulePreview call), Check 2, and Check 3 — and record a per-candidate verdict: PASS / DROP / FIX, with the exact sub-tx and parent-tx counts. So 10 candidates → 10 preview calls → 10 verdicts.

Act on the results:

• DROP any candidate that matches 0 sub-txs (the rule would do nothing).
• FIX config problems (inverted dates, min>max, identifier-on-wrong-direction,

mutually-exclusive prefixes, bad cutoffTime).

• Note any overlap with another candidate or an Active/Pending rule in the report —

overlap is informational (the engine resolves it deterministically by id), so only adjust if the user prefers cleaner separation; do not drop on overlap alone.

Candidates that DROP or have unresolved FIXes don't proceed to Step 3. This gate is what keeps suggestion quality high — do not skip it.

Naming rollup rules

Every proposed rule needs a clear, consistent name. Decide it like this:

1. Match the org's existing convention first. From the Active/Pending rule names you

fetched in Step 1b, infer the org's pattern — separator, field order, casing, how they denote direction/fees/interval — and name new rules the same way so they sit naturally alongside the existing ones.

1. If there's no clear existing pattern, default to:

<wallet name> - <asset symbol> - <direction> <fees label> and append (<interval>), where the fees label maps:

• fees: ONLY → fees (e.g. "gas fees")
• fees: INCLUDE → include fees
• fees: EXCLUDE → exclude fees

Example: EVM Exec Wallet 1 - ETH - outflow fees (monthly). When a single discriminating filter defines the rule (e.g. a known method), fold it into the name (e.g. … - LP exits (daily)).

Keep names human-readable and unique within the proposal set. Use the same name in the HTML report, the proposal table, and the name field of the create mutation.

Step 3 — Present Results

3a. HTML proposal report

Write a standalone .html file to the working directory (e.g. rollup-rules-proposal.html) and tell the user the path so they can open it. Use the template and patterns in references/proposal-html-template.html verbatim — copy the CSS and skeleton as-is, only replacing the <!-- PLACEHOLDER --> comments with actual data rows. Do NOT regenerate the CSS or layout. That reference file documents the summary cards, the proposed-rules table, the skipped table, the per-candidate "Preview matched txs" ledger link, the impact badges, and the hash/address display rule. Keep the HTML compact (target under 4000 tokens of body).

Key content rules from that reference, called out here because they matter:

• The Volume column is always Volume (sub-tx / tx) and values are always prefixed

with ~ (e.g. ~1,240 / ~310) — the values are the rollup_review-validated sub-tx and distinct parent-tx counts, and ~ sets the expectation that the Preview link's ledger filters can't express every rule filter exactly.

• Impact badges: high volume is a GOOD result, never an alarm — green HIGH / indigo

MEDIUM / grey LOW. Red is reserved for actual problems (the 🟢/🟡/🔴 validation status), never for impact.

• Skipped table: include candidates the rollup_review gate dropped (e.g. "0 matching

sub-txs", "overlaps rule #38211").

3b. Proposal task table

Present a numbered markdown table in chat — one row per proposed rule — so the user can approve by number. Columns: #, Rule Name, Wallet (id), Asset / Platform, Direction, Filter, Volume (sub-tx / tx), Interval, Validated Impact. Priority hint: HIGH for >1000 sub-txs, MEDIUM for 200–1000, LOW for <200.

Step 4 — User Review

Ask the user:

"I've proposed X rollup rules (all validated against real transactions). Review the

report and table above. You can:"

- Approve all — I'll create all proposed rules

- Approve specific rules — tell me which numbers

- Provide feedback — tell me what to adjust and I'll re-analyze

- Cancel — no rules will be created

Wait for the user's response before proceeding. Never create a rule without explicit confirmation.

Step 5 — Create Rules

For approved rules, run the createSubTransactionRollupRules mutation via the MCP execute tool (it accepts a batch and returns per-rule results with validation issues):

mutation CreateRollupRules($rules: [RollupRuleCreationRequest]!) {
  createSubTransactionRollupRules(rules: $rules) {
    results {
      rollupRuleId
      validationIssues { blocking type message }
    }
  }
}

Each entry in $rules (all camelCase):

{
  "name": "ETH outflow gas — wallet-1 (daily)",
  "interval": "DAY",
  "createdBy": "AI",
  "rule": {
    "internalAccountId": 123,
    "assetId": "ethereum_native",
    "platform": "ETHEREUM",
    "balanceFactor": "OUTFLOW",
    "fees": "ONLY",
    "methodIds": ["0x573ade81"]
  }
}

• Always set `createdBy: "AI"` so the rule is attributed to AI in the audit trail.
• Omit `startDate` / `endDate` unless the user wants the rule bounded — omitting them

makes the rule open-ended.

• Only include optional filter fields the user/analysis actually set — do NOT send

null for unused optional fields, just omit them from the rule object.

• Prefer creating new rules. Editing an existing PENDING rule (via top-level

ruleId: <id>) is supported, but pending rules may be auto-approved after a delay, so an in-place edit can race with activation — only edit pending when the user explicitly asks.

Enum values (GraphQL enums, NOT quoted strings, in the query):

• interval: DAY or MONTH
• platform: UPPERCASE — ETHEREUM, BASE, SOLANA, BITCOIN, …
• balanceFactor: INFLOW (incoming, +1) or OUTFLOW (outgoing, -1)
• fees: INCLUDE (txs + their fees), EXCLUDE (txs without fees), ONLY (only the fee

sub-txs — selects GAS and FEE). For a gas/fee rollup use fees: ONLY by itself; do NOT also set subtxType: GAS/FEE — ONLY already covers them, and adding subtxType: GAS is redundant and wrongly drops the FEE sub-txs.

• subtxType: a FinancialAction enum or null — e.g. REWARD, NATIVE_TRANSFER,

TOKEN_TRANSFER. Leave null for gas/fee rollups (use fees: ONLY instead).

• createdBy: AI

Platform casing: lowercase in query filters (subTransaction(asset_In: [...]), asset(platform: "ethereum")); UPPERCASE enum in mutation inputs (rule.platform: ETHEREUM). Query return values are UPPERCASE too.

Validation rules the server enforces (never propose a rule that breaks these):

• senderIdentifier is only valid on INFLOW rules; recipientIdentifier only on

OUTFLOW rules (on an outflow the sender is always your wallet, and vice versa).

• senderIdentifier ⊥ originalSenderPrefix; recipientIdentifier ⊥

originalRecipientPrefix (mutually exclusive).

• startDate must be before endDate.
• An identical rule (same rule JSON) cannot already exist for the org.

The mutation also re-checks matching transactions and overlaps and returns those as validationIssues — the rollup_review gate should have caught them already, but the server is the final authority.

Resolving assetId and internalAccountId

• internalAccountId (integer): from the Step 1 wallet inventory.
• assetId is the asset key = "<platform_lowercase>_<identifier>". Native tokens:

ethereum_native, base_native, solana_native. ERC-20: ethereum_0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48 (USDC). Step 2a already returns keys in the groupKey; otherwise look them up:

query AssetKeys { asset(key_In: ["ethereum_native"]) { results { key identifier platform symbol name parentPlatform } } }

Step 6 — Report Outcomes

For each per-rule result in the batch response, color-code the outcome so the user sees status at a glance — 🟢 green = created with no issues, 🟡 yellow = created with non-blocking validation issues, 🔴 red = blocked / not created:

• rollupRuleId present, no validationIssues → 🟢 created
• rollupRuleId present with only non-blocking validationIssues → 🟡 created, issue noted
• any validationIssues with blocking: true (no rollupRuleId) → 🔴 FAILED, quote the

message

Created rules start in PENDING status and activate on the next processing cycle. Use the same 🟢/🟡/🔴 coding in the Step 3 report when surfacing the rollup_review validation outcome per proposed rule.

A. List existing rollup rules

When the user just wants to see current rules:

query ListRollupRules($limit: Int, $offset: Int, $status_In: [String]) {
  subTransactionRollupRule(limit: $limit, offset: $offset, status_In: $status_In) {
    totalCount
    results { id name interval startDate endDate nextActivationDate status rule }
  }
}

Variables: {"limit": 50, "offset": 0} (add status_In: ["Active"] etc. to filter; status is title-case). Present as a numbered markdown table: Name, ID, Status, Interval, Date range (or "indefinite"), and the key rule filters (wallet, asset, direction, fees, any optional filter). Paginate if totalCount > 50.

C. Delete rollup rules

Only PENDING rules can be deleted via the API. Active rules require TRES support.

First list the rules (Section A) so the user can identify which to delete, then confirm the rule ID(s) before deleting.

mutation DeleteRollupRules($ruleIds: [Int]!) {
  deleteSubTransactionRollupRules(ruleIds: $ruleIds) {
    results { deletedIds failures { ruleId reason } }
  }
}

Report deletedIds (succeeded) and failures (with reasons — typically the rule is already active).

Rule Field Reference (RollupRule)

Required: internalAccountId (int), assetId (asset key), platform (enum), balanceFactor (INFLOW/OUTFLOW), fees (INCLUDE/EXCLUDE/ONLY).

Optional (have safe defaults — only set when needed): senderIdentifier, recipientIdentifier, originalSenderPrefix, originalRecipientPrefix, methodIds (list), maxAmount, minAmount, excludeFiat (default false), excludeInternal (default false), subtxType (FinancialAction), bufferInDays (default 0; days to wait for late-arriving txs), cutoffTime ("HH:MM"), rollupInternalTransfersOnly (default false; when true, only internal transfers are rolled up and the rollup is paired with its inflow — the system also sets mergeWithInflowTx and runInternalTransferClassificationOnRollups).

Top-level request fields: name (required), interval (required), rule (required), startDate (optional), endDate (optional), ruleId (optional — edit a pending rule), createdBy (set AI).

FinancialAction enum values (for `subtxType`): TRACE_TRANSFER, TOKEN_TRANSFER, NATIVE_TRANSFER, DELEGATION, UNDELEGATION, VEST, UNVEST, VALIDATOR_CREATION, REWARD, COMMISSION, GAS, FEE, EXCHANGE_WITHDRAWAL, EXCHANGE_DEPOSIT, EXCHANGE_TRANSFER, EXCHANGE_BUY, EXCHANGE_SELL, EXCHANGE_LOAN, EXCHANGE_SETTLEMENT, REBATE, FIAT_TRANSFER, BURNED, ROLLUP, ROLLUP_FEE, PLUG, GROUP, FUNDING, INTEREST, TRANSFER_DELEGATION_REWARD, REEVALUATION, PAYMENT, BANK_DEPOSIT, BANK_WITHDRAWAL, MINING_REWARD.

Rules

• KEEP CONTEXT SMALL — use aggregations, never fetch full result sets.
• Run discovery queries in parallel where possible.
• ALWAYS run the Step 2.5 rollup_review gate before presenting.
• ALWAYS produce both the HTML report AND the proposal table after analysis.
• Explain your reasoning for each proposed rule.
• Always confirm before creating — present the full proposal and wait for explicit

approval before calling the create mutation.

• Provide a brief conversational summary after presenting the report.
• Incorporate user clustering guidance when choosing dimensions.

Limitations — not available via MCP

1. Editing active rules — there is no edit for an active rule; recreate (PENDING rules

can be edited via ruleId, or deleted and recreated).

1. Activating/deactivating rules — managed by the backend processing pipeline, not

directly controllable via API.

1. Viewing rollup breakdown — the detailed breakdown of which raw transactions were

aggregated is in the Rollup Breakdown report in the TRES dashboard.

1. Active rule deletion — only PENDING rules can be deleted via the API; direct the

user to TRES support for active rules.