release: set final PyPI distribution name

Author: ppradyoth

.github/workflows/publish.yml

@@ -21,7 +21,7 @@ jobs:
       id-token: write
     environment:
       name: pypi
-      url: https://pypi.org/p/agent-injection-benchmark
+      url: https://pypi.org/p/agent-injection-benchmark-test
     steps:
       - uses: actions/checkout@fbc6f3992d24b796d5a048ff273f7fcc4a7b6c09 # v5
         with:

README.md

@@ -176,7 +176,7 @@ The evaluator itself has no model-provider dependency. A plain install is
 enough for scoring a submitted JSONL or using the built-in detectors:
 
 ```bash
-pip install agent-injection-benchmark
+pip install agent-injection-benchmark-test
 aib-score --detector control_channel_scanner
 ```
 
@@ -194,7 +194,7 @@ The CLI also supports `--max-asr`, `--max-fpr`, and
 `--min-balanced-accuracy`. See [SUBMITTING.md](SUBMITTING.md) for the result
 format and [integration examples](docs/integrations.md) for wiring in an agent.
 
-Install `agent-injection-benchmark[anthropic]`, `[openai]`, or `[space]` only for
+Install `agent-injection-benchmark-test[anthropic]`, `[openai]`, or `[space]` only for
 the workflow you need.
 
 Prediction files are checked against the dataset before scoring. Duplicate IDs

SUBMITTING.md

@@ -12,7 +12,7 @@ as `blocked`, `allowed`, `malicious`, and `benign`.
 Run the local checks before opening a submission:
 
 ```bash
-pip install agent-injection-benchmark
+pip install agent-injection-benchmark-test
 aib-score --predictions predictions.jsonl --name "My guardrail" --json > result.json
 aib-validate --predictions predictions.jsonl
 ```

generation/providers/anthropic_provider.py

@@ -12,7 +12,7 @@ def __init__(self, model: str = "claude-sonnet-4-6", **kwargs):
         except ImportError as exc:
             raise ImportError(
                 "Anthropic provider requires the anthropic package. "
-                "Install with: pip install agent-injection-benchmark[anthropic]"
+                "Install with: pip install agent-injection-benchmark-test[anthropic]"
             ) from exc
         self.model = model
         self._client = anthropic.Anthropic()

generation/providers/openai_provider.py

@@ -1,4 +1,4 @@
-"""OpenAI provider stub — install with `pip install agent-injection-benchmark[openai]`."""
+"""OpenAI provider stub — install with `pip install agent-injection-benchmark-test[openai]`."""
 
 from generation.providers import BaseLLMProvider, register_provider
 
@@ -12,7 +12,7 @@ def __init__(self, model: str = "gpt-4o", **kwargs):
         except ImportError:
             raise ImportError(
                 "OpenAI provider requires the openai package. "
-                "Install with: pip install agent-injection-benchmark[openai]"
+                "Install with: pip install agent-injection-benchmark-test[openai]"
             )
         self.model = model
         self._client = openai.OpenAI()

pyproject.toml

@@ -1,5 +1,5 @@
 [project]
-name = "agent-injection-benchmark"
+name = "agent-injection-benchmark-test"
 version = "0.2.0"
 description = "A benchmark for evaluating prompt injection attacks in agentic tool-use pipelines"
 readme = "README.md"
@@ -35,7 +35,7 @@ dev = [
     "pytest>=8.0.0",
 ]
 security = ["pip-audit>=2.7.0"]
-all = ["agent-injection-benchmark[anthropic,openai,space,dev,security]"]
+all = ["agent-injection-benchmark-test[anthropic,openai,space,dev,security]"]
 
 [project.scripts]
 aib-generate = "generation.generate:main"

runtime/cli.py

@@ -33,7 +33,7 @@ def _manifest(
     count: int,
 ) -> dict[str, Any]:
     return {
-        "runner": "agent-injection-benchmark",
+        "runner": "agent-injection-benchmark-test",
         "runner_version": "0.2.0",
         "adapter": args.adapter,
         "dataset": str(data_path),