correct typos

Author: knielsen404

docs/guardrails/copyright.md

@@ -7,7 +7,7 @@ title: Copyrighted Content
 Copyright Compliance in Agentic Systems
 </div>
 
-It is important to ensure that content generated by agentic systems respects intellectual property rights and avoids the unauthorized use of copyrighted material. Copyright compliance is essential not only for legal and ethical reasons, but also to protect users and organizations from liability and reputational risk.
+It is important to ensure that content generated by agentic systems respects intellectual property rights and avoids the unauthorized use of copyrighted material. Copyright compliance is essential not only for legal and ethical reasons but also to protect users and organizations from liability and reputational risk.
 
 Guardrails provides the `copyright` function to detect if any licenses are present in a given piece of text, to protect against exactly this.
 
@@ -32,7 +32,7 @@ Detects copyrighted text material if it is in `data` and returns the detected li
 | `List[str]` |  List of detected copyright types. For example, `["GNU_AGPL_V3", "MIT_LICENSE", ...]`|
 
 ### Detecting copyrighted content
-The simplest use-case of the `copyright` function is to apply it directly to messages, as seen below.
+The simplest use-case of the `copyright` function is to apply it to all messages, as seen below.
 
 **Example:** Detecting copyrighted content
 ```guardrail

docs/guardrails/images.md

@@ -6,7 +6,7 @@ description: Secure images given to, or produced by, your agentic system.
 # Images
 
 <div class='subtitle'>
-Secure images given to, or produced by, your agentic system.
+Secure images given to, or produced by your agentic system.
 </div>
 
 At the core of computer vision agents is the ability to perceive their environment through images, typically by taking screenshots to assess the current state. This visual perception allows agents to understand interfaces, identify interactive elements, and make decisions based on what they "see."
@@ -49,7 +49,7 @@ Given an image as input, this parser extracts and returns the text in the image
 | `List[str]` | A list of extracted pieces of text from `data`. |
 
 ### Analyzing Text in Images
-The `ocr` function is a  <span class="parser-badge" size-mod="small"></span> so it returns the data found from parsing its content; in this case any text present in an image will be extracted. The extracted text can then be used for further detection, for example detecting a prompt injection in an image, like the example below.
+The `ocr` function is a  <span class="parser-badge" size-mod="small"></span> so it returns the data found from parsing its content; in this case, any text present in an image will be extracted. The extracted text can then be used for further detection, for example detecting a prompt injection in an image, like the example below.
 
 **Example:** Image Prompt Injection Detection.
 ```python
@@ -100,7 +100,7 @@ raise "Found Prompt Injection" if:
     # Only check user messages
     msg.role == 'user'
 
-    # Use image function to get images
+    # Use the image function to get images
     ocr_results := ocr(image(msg))
 
     # Check both text and images

docs/guardrails/moderation.md

@@ -38,7 +38,7 @@ Detector which evaluates to true if the given data should be moderated.
 
 | Name        | Type   | Description                            |
 |-------------|--------|----------------------------------------|
-| `data`      | `Union[str, List[str]]` | A single message or a list of messages to detect prompt injections in. |
+| `data`      | `Union[str, List[str]]` | A single message or a list of messages. |
 | `model`     | `Union[str, List[str]]` |  The model to use for moderation detection. |
 | `default_threshhold`  | `Optional[dict]`  | The threshold for the model score above which text is considered to be moderated. |
 | `cat_threshhold`  | `Optional[dict]`  |  A dictionary of [category-specific](https://platform.openai.com/docs/guides/moderation#quickstart) thresholds. |

docs/guardrails/pii.md

@@ -8,15 +8,15 @@ description: Detect and manage PII in traces.
 Detect and manage PII in traces.
 </div>
 
-Personally Identifiable Information (PII) refers to sensitive information — like names, emails, or credit card numbers — that AI systems and agents need to handle carefully. When these systems work with user data, it is important to establish clear rules about how personal information can be handled, to ensure the sytem functions safely.
+Personally Identifiable Information (PII) refers to sensitive information — like names, emails, or credit card numbers — that AI systems and agents need to handle carefully. When these systems work with user data, it is important to establish clear rules about how personal information can be handled, to ensure the system functions safely.
 
 <div class='risks'/> 
 > **PII Risks**<br/> 
 > Without safeguards, agents may: 
 
 > * **Log PII** in traces or internal tools 
 >
-> * **Expose PII** to in unintentional or dangerous ways
+> * **Expose PII** in unintentional or dangerous ways
 >
 > * **Share PII** in responses or external tool calls
 
@@ -29,13 +29,13 @@ def pii(
     entities: Optional[List[str]]
 ) -> List[str]
 ```
-Detector to find personally-identifiable information in text.
+Detector to find personally identifiable information in text.
 
 **Parameters**
 
 | Name        | Type   | Description                            |
 |-------------|--------|----------------------------------------|
-| `data`      | `Union[str, List[str]]` | A single message or a list of messages to detect PII in. |
+| `data`      | `Union[str, List[str]]` | A single message or a list of messages. |
 | `entities`  | `Optional[List[str]]`   | A list of [PII entity types](https://microsoft.github.io/presidio/supported_entities/) to detect. Defaults to detecting all types. |
 
 **Returns**
@@ -172,7 +172,7 @@ raise "Found Credit Card information in message" if:
 
 
 ### Preventing PII Leakage
-It is also possible to use the `pii` function in combination with other filters to get more complex behaviour. The example below shows how you can detect when an agent attempts to send emails outside of your organisation. 
+It is also possible to use the `pii` function in combination with other filters to get more complex behavior. The example below shows how you can detect when an agent attempts to send emails outside of your organisation. 
 
 **Example:** Detecting PII Leakage in External Communications.
 ```guardrail

docs/guardrails/secrets.md

@@ -7,7 +7,7 @@ title: Secret Tokens and Credentials
 Prevent agents from leaking sensitive keys, tokens, and credentials.
 </div>
 
-Agentic systems often operate on user data, call APIs, or interface with tools and environments that require access credentials. If not properly guarded, these credentials — such as API keys, access tokens, or database secrets — can be accidentally exposed through system outputs, logs, or responses to user prompts.
+Agentic systems often operate on user data, call APIs, or interface with tools and environments that require access credentials. If not adequately guarded, these credentials — such as API keys, access tokens, or database secrets — can be accidentally exposed through system outputs, logs, or responses to user prompts.
 
 This section describes how to detect and prevent the unintentional disclosure of secret tokens and credentials during agent execution.
 
@@ -61,12 +61,12 @@ raise "Found Secrets" if:
 ### Detecting specific secret types
 In some cases, you may want to detect only certain types of secrets—such as API keys for a particular service. Since the `secrets` detector returns a list of all matched secret types, you can check whether a specific type is present in the trace and handle it accordingly.
 
-**Example:** Detecting a github token in messages
+**Example:** Detecting a GitHub token in messages
 ```python
 from invariant.detectors import secrets
 
 raise "Found Secrets" if:
     (msg: Message)
     "GITHUB_TOKEN" in secrets(msg)
 ```
-<div class="code-caption">Specifically check for github tokens in any message.</div>
+<div class="code-caption">Specifically check for GitHub tokens in any message.</div>