> ## Documentation Index
> Fetch the complete documentation index at: https://docs.kodus.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Kodus Review

> Measure how effective Kodus's reviews are — and act on it

## What is the Kodus Review tab

The **Kodus Review** tab answers one question: *is your team acting on what Kodus says?*

Unlike the Productivity tab (which measures general delivery metrics like deploy frequency and PR cycle time), Kodus Review is about Kodus itself — how many suggestions get implemented, which categories and rules land or get ignored, and where the team pushes back.

Every chart and table respects the global **repository** and **date range** filters at the top of the page. Click a repository row, a category bar, or a rule to drill into the underlying suggestions.

## Summary cards

| Card                                | What it means                                                                                      |
| ----------------------------------- | -------------------------------------------------------------------------------------------------- |
| **Implementation rate**             | % of sent suggestions the team implemented in the period                                           |
| **Suggestions sent**                | How many suggestions Kodus delivered (as PR comments) in the period                                |
| **Negative vote rate**              | Share of reactions that were 👎, with the trend vs. the previous period                            |
| **Criticals ignored in merged PRs** | Critical suggestions left unimplemented on PRs that were already merged — the actionable risk list |

## Implementation rate

The core metric. A suggestion counts as **implemented** when its final status is `implemented` or `partially_implemented` at the time the PR closes.

```
Implementation rate = implemented suggestions ÷ sent suggestions
```

Scope rules — the same across every implementation-rate chart:

* Only **delivered** suggestions count (the ones actually posted as PR comments). Drafts Kodus filtered out before commenting are never counted.
* Suggestions are attributed to the **week the PR closed**, because implementation status is only final once the PR merges.

### Week over week

The weekly chart shows the trend, with a toggle:

* **Overall** — a single implementation-rate line.
* **By severity** — one line per severity (critical / high / medium / low), so you can see whether higher-severity suggestions get implemented more.

### By category and by severity

* **By category** — sent vs. implemented per suggestion category. Click a bar to open the suggestions explorer filtered to that category.
* **By severity** — implementation rate per severity level. The expectation is a descending gradient (critical implemented more than low). If it looks flat or inverted, severity isn't guiding the team.

<Warning>
  **The "All / Kodus only" toggle on the severity chart matters.** A Kody Rule carries the severity *you* set on the rule, not a risk assessment by Kodus. Mixing the two distorts the calibration read — for example, a pile of medium Kody Rules with high adoption can make Kodus look like it under-rates medium. Switch to **Kodus only** to see Kodus's own severity calibration. Bars built on very few suggestions are faded and marked with `*` — a 0% or 100% from a handful of suggestions is not a real signal.
</Warning>

## Negative feedback

Feedback comes from 👍 / 👎 reactions on Kodus's suggestion comments.

* **Negative vote rate** (summary card) — `👎 ÷ (👍 + 👎)`, with the trend vs. the previous period. Lower is better.
* **By category** — where the team disagrees most. A category with many 👎 is a candidate to retune or disable.
* **Trend** — negative votes week over week.

## Repositories — health

A per-repository table: PRs reviewed, suggestions sent, implementation rate, 👍/👎, and the **weakest category** (the category with the lowest implementation rate in that repo, given a minimum sample). It shows where Kodus is landing versus being ignored.

Clicking a row focuses the whole cockpit on that repository (same as picking it in the repository filter).

## Kody Rules — health

How each Kody Rule is performing in the period: triggers, implementation rate, 👍/👎, and a status. Only active rules appear — deleted or inactive ones are excluded since you can't act on them.

The status is computed per rule, in this priority order:

| Status       | Meaning                                                     | Suggested action                                                     |
| ------------ | ----------------------------------------------------------- | -------------------------------------------------------------------- |
| **Stale**    | No triggers in the period                                   | Review whether the rule is still needed                              |
| **Low data** | Triggered, but too few times (fewer than 5) to judge        | Wait for more data                                                   |
| **Noisy**    | The team actively downvotes it (≥ 3 👎 and more 👎 than 👍) | The rule is miscalibrated — rewrite or scope it (e.g. exclude tests) |
| **Ignored**  | Triggers a lot but almost nothing is implemented (≤ 20%)    | Question its relevance — does the team care about it?                |
| **Healthy**  | Everything else                                             | No action                                                            |

**Noisy** and **Ignored** look similar but call for different actions. *Ignored* is passive — the rule fires but nobody implements it, and you can't tell if it's noise or just neglect. *Noisy* is active disagreement — the team explicitly downvotes it, so you know it's noise. That's why a rule that is both shows as **Noisy**: the downvotes are the stronger, more actionable signal. The thresholds are sensible defaults and may be tuned over time.

## Suggestions explorer

Every drill-down — a category bar, a rule row, the "criticals ignored" card — opens the **suggestions explorer**: a filterable, paginated list of the actual suggestions behind the number.

Filters: repository, category, severity, implementation status, Kody Rule, and free-text search. Each row expands to show the existing vs. suggested code and a link to the PR comment.