---
license: cc-by-4.0
task_categories:
- question-answering
- text-generation
language:
- en
tags:
- finance
- erp
- benchmark
- agents
- mcp
- deterministic-evaluation
pretty_name: LedgerBench-100
size_categories:
- n<1K
---

# LedgerBench-100

LedgerBench-100 is a deterministic corporate-finance agent benchmark: 100 tasks over a
shared simulated finance world (a D365-shaped ERP, an Odoo-shaped procure-to-pay and
manufacturing surface, a QBO-style subsidiary ledger, a shared drive, email, document
management, and frozen real SEC XBRL filings) served through 8 MCP
servers exposing 66 tools. Tasks are in-fiction persona chat messages;
the graded answer contract is discovered through the harness server's `reporting_fields`
tool, the way a real reporting system's schema is read before filing into it.

Grading is fully deterministic and binary — answer checks with typed tolerances, trace
checks (required servers, reads before submission), and state checks that grade the world
the agent leaves behind (committed payment runs, paid/rejected partitions, reason codes)
plus a `writes_only` anti-hack veto. No LLM judge, no network, no clock in the reward path.

## Measured contents

- Tasks: 100 across 22 families: anomaly_triage (1), bank_rec (4), business_brief (3), business_brief_fb (3), cash_app (3), cash_forecast (2), close_mgmt (6), collections_ops (1), cross_system (7), erp_qa (11), erp_qa_fb (5), erpbench (10), expense_audit (4), finance_qa (10), finance_qa_fb (2), fpna (5), journal_entry (2), payment_proposal (2), payment_run (3), pbc (4), threeway_match (5), vendor_master (7)
- Oracle walk length: min 3 / median 6 / max 104 MCP calls (1515 total)
- Checks: 434 answer + 257 trace + 264 state = 955 graded checks
- Context files: 59 seeded documents/inputs (36 unique) across 47 tasks; most context lives inside the world itself (ERP rows, workbooks, emails, filings)
- Escalated variants: 30 tasks are escalations of a base task also in the release; 25 of them (`doc_mode = "buried"`) deliberately reuse the base persona message verbatim against a harder world — the governing policy must be found among seeded decoy documents — so those prompt texts appear twice by design
- Prompt uniqueness across the 75 distinct prompts: maximum pairwise 5-shingle Jaccard 0.91411

## What is included

- `data/tasks.jsonl`: apex-accounting-compatible records (`task_id`, `task_name`, `world_id`, `prompt`, `context_files`, `rubric`, `gold_output`, `metadata`).
- `tasks/`: one readable JSON record per task.
- `task_files/`: seeded per-task context documents and input files.
- `world/`: the world source — MCP framework, the eight servers, the deterministic verifier engine, the Streamable HTTP bridge, and the full SQL schema.
- `trajectories/`: one normalized oracle MCP trajectory per task.
- `reports/`: measured build and qualification evidence.

The runnable form is the Harbor dataset `blobfishai/ledgerbench-100`: self-contained
task packs (prepared SQLite world + runtime on a digest-pinned `python:3.12-slim`)
whose `tests/test.sh` calls a token-gated `/verify` endpoint; the agent container
never sees the verification token.

## Measured qualification (600 executions)

| Gate | Result |
|---|---:|
| Oracle replays | 100/100 reward 1.0 |
| Deterministic replays (byte-identical reports) | 100/100 |

| Negative control | Executions | False accepts |
|---|---:|---:|
| no_submit | 100 | 0 |
| noop | 100 | 0 |
| off_task_write | 100 | 0 |
| wrong_submit | 100 | 0 |

Full per-task evidence is in `reports/qualification.json`; do not infer a model score
from the oracle trajectories.

## Data provenance and contamination

The company, its customers, vendors, employees, balances, and documents are synthetic
(FinanceBenchmark-derived journal shapes with synthetic entities). The `filings` surface
serves frozen real SEC XBRL facts (38 registrants, snapshot-pinned) — real public data,
included under its own public-domain terms. Task text and gold answers are original to
this release's source repository. Gold outputs are public, so this release suits
transparent evaluation and RL experiments rather than secret-test claims.

## Licenses

Task data and documents are CC-BY-4.0. Benchmark code and harnesses are
Apache-2.0. SEC XBRL facts are US-government public-domain data.