DOC: Scoring Docs Refactor (#1892)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Author: rlundeen2

doc/blog/2025_01_27.md

@@ -82,7 +82,7 @@ When examining this request, you may discover that occasionally the Adversarial
 
 [^8]: "PyRIT - SearchReplaceConverter", ../api/pyrit_prompt_converter.md#searchreplaceconverter
 
-[^9]: "PyRIT - True False Scoring", ../code/scoring/2_true_false_scorers.ipynb#true-false-scoring
+[^9]: "PyRIT - True False Scoring", ../code/scoring/1_true_false_scorers.ipynb
 
 ### Final Thoughts
 

doc/blog/2026_04_14_scoring_scorers.md

@@ -108,7 +108,7 @@ flowchart TB
 
 There are a few different ways to view metrics for specific scoring configurations.
 
-**Directly on a scorer instance:** Call `get_scorer_metrics()` on any scorer object to look up its saved metrics (if they exist), as described at the bottom of the [Scorer Evaluation Identifier](#scorer-evaluation-identifier) section above. See the [scorer metrics notebook](../code/scoring/7_scorer_metrics.ipynb) to try it yourself!
+**Directly on a scorer instance:** Call `get_scorer_metrics()` on any scorer object to look up its saved metrics (if they exist), as described at the bottom of the [Scorer Evaluation Identifier](#scorer-evaluation-identifier) section above. See the [scorer metrics notebook](../code/scoring/4_scorer_metrics.ipynb) to try it yourself!
 
 **Automatically in scenario output:** When running scenarios and printing results (i.e., in [pyrit_scan](../scanner/1_pyrit_scan.ipynb) or [pyrit_shell](../scanner/2_pyrit_shell.md)), metrics are automatically fetched and displayed alongside the attack results (as long as the scoring configuration has been evaluated before):
 
@@ -132,7 +132,7 @@ The framework checks the JSONL registry for an existing entry matching the score
 
 ![alt text](2026_04_14_running_evaluation.png)
 
-For the full walkthrough — including running objective and harm evaluations, configuring custom datasets, and comparing results — give the [scorer metrics notebook](../code/scoring/7_scorer_metrics.ipynb) a try!
+For the full walkthrough — including running objective and harm evaluations, configuring custom datasets, and comparing results — give the [scorer metrics notebook](../code/scoring/4_scorer_metrics.ipynb) a try!
 
 ## Closing Thoughts
 

doc/code/framework.md

@@ -108,7 +108,7 @@ Ways to contribute: Check out our [target docs](./targets/0_prompt_targets.md).
 
 The scoring engine is a component that gives feedback to the attack on what happened with the prompt. This could be as simple as "Was this prompt blocked?" or "Was our objective achieved?"
 
-Ways to contribute: Check out our [scoring docs](./scoring/0_scoring.md). Is there data you want to use to make decisions or analyze?
+Ways to contribute: Check out our [scoring docs](./scoring/0_scoring.ipynb). Is there data you want to use to make decisions or analyze?
 
 ## Memory
 

doc/code/memory/5_advanced_memory.ipynb

@@ -172,7 +172,7 @@
    "id": "2",
    "metadata": {},
    "source": [
-    "Because you have labeled `group1`, you can retrieve these prompts later. For example, you could score them as shown [here](../scoring/6_batch_scorer.ipynb). Or you could resend them as shown below; this script will resend any prompts with the label regardless of modality."
+    "Because you have labeled `group1`, you can retrieve these prompts later. For example, you could score them as shown [here](../scoring/0_scoring.ipynb#batch-scoring). Or you could resend them as shown below; this script will resend any prompts with the label regardless of modality."
    ]
   },
   {

doc/code/memory/5_advanced_memory.py

@@ -63,7 +63,7 @@
     await output_attack_async(result)
 
 # %% [markdown]
-# Because you have labeled `group1`, you can retrieve these prompts later. For example, you could score them as shown [here](../scoring/6_batch_scorer.ipynb). Or you could resend them as shown below; this script will resend any prompts with the label regardless of modality.
+# Because you have labeled `group1`, you can retrieve these prompts later. For example, you could score them as shown [here](../scoring/0_scoring.ipynb#batch-scoring). Or you could resend them as shown below; this script will resend any prompts with the label regardless of modality.
 
 # %%
 from pyrit.executor.attack import AttackConverterConfig