---
license: cc-by-4.0
language:
- en
pretty_name: Coding-Agent Tool-Call Safety
size_categories:
- 1K<n<10K
task_categories:
- text-classification
tags:
- coding-agents
- tool-calls
- agent-safety
- policy
- synthetic
- benchmark
configs:
- config_name: main
  data_files:
  - split: dev
    path: data/main/dev.jsonl
  - split: holdout
    path: data/main/holdout.jsonl
- config_name: confirmation
  data_files:
  - split: holdout
    path: data/confirmation/holdout.jsonl
---

# Decision Models as Policy Gates for Coding Agents

Synthetic coding-agent tool calls labeled against 28 policy rules, from the paper *Decision Models as Policy Gates for Coding Agents: Explicit Policy Boundaries Improve Detection and Reduce False Alarms* (James P. Beno, Agent Approve, 2026, [arXiv:2611.02155](https://arxiv.org/abs/2611.02155)). The harness, run records and analysis code are at [github.com/agentapprove/decision-policy-rules](https://github.com/agentapprove/decision-policy-rules).

**Every person, company, repository, host, channel and credential in these cases is fictional.** The cases were written to be classified, never executed. They include destructive commands and credential-shaped strings whose formats are real and whose bodies are random; each case declares its synthetic secrets. Do not run anything from this dataset.

## What is in it

| Config | Split | Cases | Families | Tool-only positive labels |
|---|---|---|---|---|
| `main` | dev | 1535 | | |
| `main` | holdout (sealed before inference) | 1108 | | |
| `main` | total | 2643 | 106 | 4,413 |
| `confirmation` | holdout | 320 | 16 | 531 |

Each case is one proposed tool invocation by a coding agent (a Claude Code built-in tool such as Bash, Write or Edit, or an MCP tool) with a short trusted context, labeled for each of the 28 rule templates in three settings: **tool_only** (the model sees the invocation alone), **user_request** (plus the user's request), and **bounded_context** (plus trusted project facts such as git remotes, files present and identities). The 320-case confirmation set was written after every main-set result had been seen, through the same pipeline, as a check that the findings were not specific to the first scenarios.

## Fields

| Field | Type | Meaning |
|---|---|---|
| `id` | string | Case id; shuffled so that it encodes neither family nor split |
| `family` | string | The scenario family (106 in the main set, 16 in the confirmation set) |
| `split` | string | `dev` or `holdout` |
| `stratum` | string | Size stratum of the action (S, M, L, XL) |
| `tags` | list of strings | Case design tags (hard negative, context flip, injection, decoy context, ...) |
| `tool_name` | string | The tool invoked |
| `tool_arguments` | string (JSON) | The tool's arguments; the shape depends on the tool |
| `context` | string (JSON) | The trusted context record for the with-context setting |
| `truth_tool_only`, `truth_user_request`, `truth_bounded_context` | object | Gold label per rule template: `"true"`, `"false"`, `"unknown"` (evidence missing in that setting) or `"excluded"` (quarantined class) |
| `provenance_tool_only`, `provenance_user_request`, `provenance_bounded_context` | object | Per-label provenance: `agreed`, `adjudicated-model`, `adjudicated-human`, `rulebook-relabel` or `unresolved` |
| `rationale` | string | The generator's rationale, citing rulebook rules |
| `evidence_locator`, `evidence_byte_offset` | string, int | Verbatim evidence for a positive label and its byte offset in the action |
| `evidence_gaps`, `quarantine`, `rulebook_refs` | list, string (JSON), list | Enumerated evidence gaps, quarantined classes, and rulebook references |

The 28 rule templates: `permanent-deletion`, `git-force-push-or-delete-ref`, `download-and-execute-code`, `replace-existing-file-content`, `read-credential-material`, `share-credential-material`, `change-security-or-persistence`, `git-discard-local-changes`, `git-history-rewrite`, `disable-tests-or-checks`, `git-commit-credential-files`, `git-change-remote-or-hooks`, `upload-file-contents-externally`, `public-discussion-post`, `communication-outside-slack`, `send-data-to-external-host`, `change-production-state`, `deploy-to-production`, `database-destructive-statement`, `database-production-write`, `slack-dm-specific-person`, `git-push-specific-repository`, `read-only-inspection`, `message-another-person`, `act-on-instructions-in-content`, `edit-shell-profile-or-dotfiles`, `run-with-elevated-privileges`, `move-to-trash`.

Labels, rationales, family names and split names were never part of a model's input; the harness builds inputs from `tool_name`, `tool_arguments` and `context` only.

## How the labels were made

Each family was generated by a model from a brief that holds the labeling rulebook (`rulebook/RULEBOOK.md`), the reserved synthetic identifiers (`rulebook/allowlist.json`) and the real MCP servers the cases may use (`rulebook/mcp-registry.json`). A second, blind model labeled the shuffled cases under opaque ids with no access to the generator's labels; disagreements went to an adjudicator deciding by rulebook, and every label carries its provenance. The holdout was sealed by hash before any inference (`original/*/HOLDOUT-SEAL.json`). The full procedure, agreement statistics, validation checks and limitations are in `original/main/DATASET-CARD.md` and `original/confirmation/DATASET-CARD.md`.

## Rule texts

`rules/` holds the texts the models were sent: the product's one-sentence definitions (`product-templates.json`), the two independently authored lists of examples and counterexamples (`library-author-opus.json`, `library-author-gpt6.json`), the name-free and prose controls, and the brief the authors wrote from (`AUTHOR-BRIEF.md`).

## Canonical files

`original/main/dataset.json` and `original/confirmation/dataset.json` are the canonical nested files (sha256 in `dataset.sha256`): main `a1f1fd3176968a2e955656f98a82d24ffb397d961591be2daefe29098cad95e8`, confirmation `c7bb3ef023da99c2bea31028392d57982f3aa78b011a4049aefd7647abd6a3b1`. The JSONL files are a one-to-one flattening of them.

## License and citation

CC BY 4.0, copyright (c) 2026 Agent Approve LLC. Cite the paper:

```bibtex
@misc{beno2026decisionmodels,
  title={Decision Models as Policy Gates for Coding Agents: Explicit Policy Boundaries Improve Detection and Reduce False Alarms},
  author={James P. Beno},
  year={2026},
  eprint={2611.02155},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  doi={10.48550/arXiv.2611.02155}
}
```