docs: adding links + descriptions to ai codacy section (#2534)

* adding links + descriptions
* add → symbols to links
* funcionality notes on AI Reviewer docs
* fix typos + grammar
* Apply suggestions from codacy's code review
Co-authored-by: codacy-production[bot] <61871480+codacy-production[bot]@users.noreply.github.com>
---------
Co-authored-by: codacy-production[bot] <61871480+codacy-production[bot]@users.noreply.github.com>

Author: claudiacodacy

docs/codacy-ai/codacy-ai.md

@@ -10,25 +10,27 @@ Codacy AI utilizes only enterprise-grade instances of OpenAI and Google Gemini s
 
 ### AI-enhanced comments
 
+_This feature leverages OpenAI models, and is strictly opt-in: it will only run on repositories or projects where a repository admin has enabled it._
+
 AI-enhanced comments are optional, machine-generated suggestions that appear directly in pull requests and review threads. They use Codacy's AI to provide concise issue summaries, remediation suggestions, and links to relevant documentation — helping reviewers and authors quickly understand and fix problems.
 
-This feature leverages OpenAI models, and is strictly opt-in: it will only run on repositories or projects where a repository admin has enabled it.
+More details about [AI-enhanced comments here →](../repositories-configure/integrations/github-integration.md#ai-enhanced-comments).
 
-How to turn it on
+**How to turn it on**
 
 1. Go to your organization or repository settings in Codacy.
 2. Navigate to the "Integrations" or "AI features" section (depending on your Codacy plan and UI version).
 3. Find "AI-enhanced comments" and toggle the feature to "On" for the repository or organization scope you want to enable.
 4. Optionally configure which repositories, branches, or severity levels should receive AI comments to reduce noise.
 5. Save your changes. Once enabled, Codacy will start adding AI-enhanced comments to new pull requests and code reviews according to the configured scope.
 
-Notes
+**Notes**
 
 - Administrators can enable or disable the feature at organization or repository level.
 - Enabling the feature may be subject to plan limitations and governance controls; check your Codacy subscription and admin permissions.
 - Users can still ignore or dismiss individual AI comments during code review.
 
-- Data usage and privacy
+**Data usage and privacy**
 
 - To generate an AI-enhanced comment, Codacy only processes the specific issue context: the issue line plus up to ten lines before and ten lines after that line. No additional repository data is sent or used.
 - Codacy does not use your code, repository contents, or comments to train external AI models. No customer code or review text is incorporated into model training.
@@ -41,34 +43,42 @@ Notes
     end="<!--paid-feature-business-end-->"
 %}
 
-This feature leverages OpenAI models, and is strictly opt-in: you need to get in touch with us in order to enable it.
+_This feature leverages OpenAI models, and is strictly opt-in: you need to get in touch with us in order to enable it._
+
+Codacy False Positive triage analyzes results on a commit basis to give you visibility into issues that may be false positives (based on their context). During triage, each issue is given a confidence score along with an explanation. When the confidence level falls below a defined threshold, the issue is then flagged as an AI false positive and surfaced for manual review. You can evaluate potential false positives during a pull request in app or on any Codacy page where issues appear. These issues can be ignored or marked as Not a false positive.
+
+More details about [False Positives here →](../repositories/commits.md#false-positive-issues).
 
-How to turn it on
+**How to turn it on**
 
 1. Get in touch with your Customer Success Manager or with <support@codacy.com>
 
-Notes
+**Notes**
 
 - Codacy does not use your code, repository contents, or comments to train external AI models. No customer code or review text is incorporated into model training.
 - To detect a Possible False Positive, Codacy only processes the specific issue context: one request per file with issues. No additional repository data is sent or used.
 - Prompts are neither stored nor visible by anyone
 
-### PR Reviewer
+### AI Reviewer
 
 !!! note
-    PR Reviewer is currently only available on GitHub, for all Team and Business plans.
+    AI Reviewer is currently only available on GitHub, for all Team and Business plans.
+
+_This feature leverages Google Gemini models, and is strictly opt-in: it will only run on repositories or projects where a repository admin has enabled it._
+
+The AI Reviewer combines the reliability of deterministic, rule-based static code analysis with the power of AI. It draws in the necessary context from source code and PR metadata to ensure the business intent matches the technical outcome, and can catch logic gaps that conventional scanners (and human reviewers) often miss.
 
-This feature leverages Google Gemini models, and is strictly opt-in: it will only run on repositories or projects where a repository admin has enabled it.
+More details about [AI Reviewer here →](../repositories-configure/integrations/github-integration.md#ai-reviewer).
 
-How to turn it on
+**How to turn it on**
 
 1. Go to your organization or repository settings in Codacy.
 2. Navigate to the "Integrations" or "AI features" section (depending on your Codacy plan and UI version).
 3. Find "AI Reviewer", under "Status checks", and toggle the feature to "On" for the repository or organization scope you want to enable.
-4. Save your changes. Once enabled, Codacy will start adding a Summary to your pull requests with of the information used to provide the AI-enriched reviews.
+4. Save your changes. Once enabled, Codacy will start adding a Summary to your pull requests based on the AI-enriched reviews.
 5. To request a PR Review from codacy, add a **`codacy-review`** label to your Pull Request. Codacy listens to the event and will publish the review as soon as it's ready.
 
-Notes
+**Notes**
 
 - Codacy does not use your code, repository contents, or comments to train external AI models. No customer code or review text is incorporated into model training.
 - To enrich the review, the git diff of the Pull Request as well as some related files' contents can be sent as context. No data is stored on our side, or used to train any models.

docs/repositories-configure/integrations/github-integration.md

@@ -32,14 +32,20 @@ Adds a report to your pull requests showing whether your pull requests and cover
 
 ### AI Reviewer
 
+!!! note
+    This feature is only supported on GitHub.
+
+    If you choose to enable the AI Reviewer, consider disabling the AI-enhanced comments, as it may duplicate any comments on Codacy issues you receive.
+
 The AI Reviewer combines the reliability of deterministic, rule-based static code analysis with the power of AI. It draws in the necessary context from source code and PR metadata to ensure the business intent matches the technical outcome, and can catch logic gaps that conventional scanners (and human reviewers) often miss.
 
 It provides feedback on missing or weak tests, complex or duplicated code, and keeps security concerns up to date. Beyond that, it adds contextual insights about whether the changes follow the requirements, business rules, and logic used in the project.
 
+This setting can be enabled at a repository or organization level. Once enabled, Codacy will start adding a Summary to your pull requests based on the AI-enriched reviews. To request a PR Review from Codacy, add a **`codacy-review`** label to your Pull Request. Codacy listens to the event and will publish the review as soon as it's ready.
+
+
 ![AI Reviewer on Github](images/github-integration-ai-reviewer.png)
 
-!!! note
-    This feature is only supported on GitHub.
 
 ### Issue annotations