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

# Ticket Analysis

> How Waterline analyzes a ticket and produces a progress score.

When you analyze a ticket, Waterline runs a pipeline that combines semantic search across your codebase with LLM-powered scoring — then produces a deterministic result from consistent thresholds.

***

## The pipeline

<Steps>
  <Step title="Fetch the ticket">
    Waterline retrieves the ticket summary, description, and acceptance criteria from Jira, GitHub Issues, or Asana.
  </Step>

  <Step title="Search the codebase">
    The ticket is used to search your indexed codebase semantically. Waterline finds the functions and classes most likely to implement the ticket's requirements.
  </Step>

  <Step title="Score relevance">
    Each candidate symbol is scored for how directly it addresses the ticket. Noise is filtered out before the next step.
  </Step>

  <Step title="Extract and map criteria">
    Waterline extracts the discrete acceptance criteria from the ticket description, then maps each piece of code evidence to the criteria it supports.
  </Step>

  <Step title="Aggregate the score">
    Each criterion is classified as SATISFIED, PARTIAL, or UNSATISFIED based on the strength of evidence. The overall score is computed from consistent, fixed thresholds — not a variable LLM output.
  </Step>
</Steps>

***

## Results are cached

Waterline caches analysis results. When a cached result is available, it returns in under a second. After each push, Waterline pre-computes code-to-ticket alignments so the next analysis is faster — but a full re-analysis only runs when you request it.

***

## What you get back

Each analysis returns:

* **Overall progress %** — the headline score
* **Per-criterion breakdown** — SATISFIED / PARTIAL / UNSATISFIED for each requirement, with a confidence level
* **Evidence list** — the specific functions and classes that support each criterion
* **Uncertainty level** — LOW, MEDIUM, or HIGH, indicating how confident Waterline is in the overall result

***

## Result example

```
PROJ-123 — Add user authentication
Progress: 73%

✅ Login endpoint validates credentials         (high confidence)
✅ JWT token issued on successful login         (high confidence)
⚠️  Password reset via email                    (partial — email sending found, expiry logic unclear)
❌ OAuth (Google) login                         (no evidence found)

Uncertainty: LOW
```