analyze_journal_variance

shallow

io.github.HelloBooksAIAgents/hellobooks-mcp · Verify this server

Compare two periods of journal-entry data (QBO or Xero — source auto-detected from headers) and flag accounts whose movement deviates materially between periods. Aggregates lines per account into a net total for each period, then surfaces accounts where the period-over-period change crosses a materiality threshold (≥5% relative AND ≥$100 absolute; severity high at ≥50%, medium at ≥20%, low at ≥5%). Inputs are two CSV exports — periodACsv (earlier period) and periodBCsv (later period). Optional periodALabel / periodBLabel for human-readable flag messages (e.g. "Q1 FY2024" vs "Q2 FY2024"). Max 5,000 rows per period; max 5 MB each. Use this when a user pastes two periods and asks "what changed?", "show me variances", "what jumped period-over-period". Returns a flag list ordered by largest delta, a roll-up, and a shareable URL. Both periods must be the same source — mixing QBO + Xero in one call returns an error.

100.0/100

1 trials · measured 8 days ago

analyze_journal_variance scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against io.github.HelloBooksAIAgents/hellobooks-mcp, measured 25 Aug 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

ComponentWeightValue
Reliability35%not applicable
Schema integrity25%100.0
Failure behaviour15%not applicable
Latency15%not applicable
Concurrency10%not applicable

Tool details

Transport
remote
Credential class
open
Input schema
not declared
Output schema
not declared
Side-effect classification
unclassified

Score history

DayScoreTierMethodology
2026-08-25100.0shallowv0.2.0

Probe evidence

ProbeOutcomes
schema_integritypass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

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Vouch score: analyze_journal_variance
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analyze_journal_variance — Vouch