Tusk Drift Analyze

You are performing local deviation analysis for Tusk Drift. Your job is to analyze API test deviations, classify them, and optionally fix regressions.

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Phase 1: Run Tests and Collect Deviations

Try running against Tusk Drift Cloud first:

tusk drift run --cloud --save-results agent --print

If the command fails with an authentication error (e.g., Error: not authenticated. Run tusk auth login or set TUSK_API_KEY):

1. Tell the user they need to authenticate and give them two options:

• Run tusk auth login to authenticate interactively
• Set the TUSK_API_KEY environment variable

1. Check if local traces exist at .tusk/traces/. If trace files are present, ask the user:

> You're not authenticated with Tusk Drift Cloud, but I found local traces in .tusk/traces/. Would you like to replay those instead?

1. If the user wants to replay local traces, drop the --cloud flag for all subsequent tusk drift run commands in this session:

``bash tusk drift run --save-results agent --print ``

Capture the output directory path printed to stderr (e.g., .tusk/results/run-20260329-140532/).

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Phase 2: Read and Understand Deviations

1. Read index.md in the output directory to get the full picture: how many tests ran, how many passed, how many failed, and the list of deviation files.

1. If there are no deviations, report that all tests passed and stop.

1. Determine the base branch:

• Check index.md for a Base Branch: line. If present, use that value.
• If not present, fall back: try main, then master (check which exists with git rev-parse --verify).

1. Get the PR diff to understand what this branch changed:

``bash git diff ...HEAD --stat git diff ...HEAD ``

If the diff is very large, use --stat first, then selectively read diffs for relevant files.

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Phase 2.5: Triage (10+ Deviations)

If there are 10 or more deviations, do NOT jump straight into analyzing each one individually. Instead, triage first:

1. Scan frontmatter only across all deviation files to build an overview. Read just the YAML frontmatter (between the --- markers) from each file — do not read the full body yet.

1. Group by endpoint — deviations on the same endpoint likely share a root cause. You only need to deeply analyze one representative per group, then apply the finding to the rest.

1. Fast-classify obvious cases — if has_mock_not_found: true and the endpoint does not appear in the PR diff, classify as UNRELATED without deep investigation. These are mock gaps, not code bugs.

1. Prioritize the remaining deviations:

• RESPONSE_MISMATCH on endpoints touched by the PR diff — most likely to be real intended/unintended changes. Analyze these first.
• NO_RESPONSE failures — investigate for crashes/deadlocks.
• Everything else — handle after the high-priority ones.

Only read the full deviation file body for deviations that require deep investigation.

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Phase 3: Analyze Each Deviation

For each deviation (or group of similar deviations) that requires analysis:

3a. Read the deviation file

Read the full .md file. Pay attention to:

• The frontmatter (endpoint, failuretype, status codes, hasmocknotfound)
• The Response Diff section (what changed in the API response)
• The Outbound Call Context table (mock match quality)
• The Mock Not Found Events section (missing mocks)

3b. Investigate the codebase

• Find the server endpoint implementation for the endpoint in the deviation
• Cross-reference with the PR diff to see what changed
• Trace the execution path that would lead to the observed deviations
• Check if outbound call changes (new calls, removed calls) explain the deviation

3c. Classify the deviation

Assign one of these types:

| Type | Meaning | | -------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | INTENDED | The deviation directly aligns with what the PR is changing. Example: PR adds a verification_required field, and the deviation shows that field appearing in the response. | | UNINTENDED | The deviation looks like a regression not matching the PR's intent. Example: PR refactors auth middleware, and an unrelated endpoint starts returning 500. | | UNRELATED | The deviation is caused by environmental factors, mock issues, or flaky behavior unrelated to PR changes. | | UNKNOWN | Cannot determine with available information. |

3d. Apply these heuristics

Mock-related heuristics (critical):

• If has_mock_not_found: true and the PR did NOT intentionally introduce the new outbound call, the deviation is likely UNRELATED — the missing mock is causing the deviation, not a code bug.
• If outbound calls matched at FALLBACK level, the response may differ due to imprecise mocking rather than a real regression. Note this and factor it into your confidence.
• If outbound calls matched at FUZZY or GLOBAL scope (from other traces), the mock data may not be representative. Lower your confidence.

NO_RESPONSE heuristics:

• During replay, ALL external dependencies (databases, HTTP calls, Redis, gRPC) are mocked and return instantly.
• Database query performance CANNOT cause timeouts during replay.
• Network latency CANNOT cause timeouts during replay.
• If failure_type: NO_RESPONSE, look for infinite loops, crashes, deadlocks, or panics in the application code itself.

General investigation guidance:

• Start by examining the server endpoint implementation
• Check the PR diff to understand what changed
• Check stack traces in outbound call context to understand call flow
• Consider how poor mock matches might cascade to server-level deviations
• Follow the execution path leading to the observed deviations

3e. Write your analysis

For each deviation, produce:

• Classification: INTENDED / UNINTENDED / UNRELATED / UNKNOWN
• Confidence: HIGH / MEDIUM / LOW
• What changed: 1-2 sentences describing the deviation
• Why it changed: 2-4 sentences explaining the root cause, citing specific file paths and line numbers
• Potential fix (if UNINTENDED): 1 sentence describing what to fix and where

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Phase 4: Present Results

After analyzing all deviations, present a summary table:

## Deviation Analysis Summary

| #   | Endpoint             | Classification | Confidence | Root Cause                                                            |
| --- | -------------------- | -------------- | ---------- | --------------------------------------------------------------------- |
| 1   | POST /api/v1/users   | INTENDED       | HIGH       | PR adds verification_required field to user creation response         |
| 2   | GET /api/v1/orders   | UNRELATED      | HIGH       | Mock not found for shipping-service; missing mock, not a code bug     |
| 3   | PUT /api/v1/settings | UNINTENDED     | MEDIUM     | Auth middleware refactor broke header propagation in settings handler |

Then provide detailed analysis for each deviation.

If there are any UNINTENDED deviations, ask the user:

> Found N unintended deviation(s) that may be regressions. Would you like me to attempt to fix them?

Wait for the user's response before proceeding to Phase 5.

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Phase 5: Fix Unintended Deviations (User-Initiated)

Only proceed if the user confirms they want fixes.

For each UNINTENDED deviation:

5a. Investigate and fix

• Look at the relevant code locations identified in Phase 3
• Propose and apply a code fix
• Explain what you changed and why

5b. Verify the fix

Re-run the specific test (drop --cloud if replaying local traces):

tusk drift run --cloud --save-results agent --print --trace-id {deviation_id}

5c. Evaluate the result

After re-running, read the new output and determine the outcome:

| Outcome | Meaning | Action | | ----------------------- | ----------------------------------- | -------------------------------------------------------------------------------------------------------------------- | | FIXED | Test passes now | Report success, move to next deviation | | DEVIATIONIDENTICAL | Same deviation persists after fix | The code change had no effect. Likely a mock gap or environmental issue. Stop and reclassify as UNRELATED/UNFIXABLE. | | DEVIATIONCHANGED | Different deviation now | Assess whether new deviation is a separate issue. Report it, don't chase it. | | NEW_DEVIATION | Original fixed but new one appeared | Flag the new deviation as separate. Don't chase it in this loop. |

5d. Iterate if needed

• Max 3 fix attempts per deviation before giving up
• Early stop: if the same deviation persists unchanged after 2 different fix approaches, stop early — the issue is likely a mock gap or environment factor, not a code bug. Don't use the third attempt.
• If a fix resolves one deviation but introduces a new one, flag it and stop

5e. Report fix results

Present a summary of fix outcomes:

## Fix Results

| #   | Endpoint             | Outcome              | Details                                                            |
| --- | -------------------- | -------------------- | ------------------------------------------------------------------ |
| 1   | PUT /api/v1/settings | FIXED                | Fixed header propagation in auth middleware                        |
| 2   | DELETE /api/v1/cache | UNFIXABLE_MOCK_ISSUE | Deviation caused by missing mock for cache-service, not a code bug |

Outcome values:

• FIXED: Code change resolved the deviation, test passes
• PARTIALLY_FIXED: Some deviations resolved but others remain
• UNFIXABLEMOCKISSUE: Deviation caused by missing or imprecise mock, not a code bug
• UNFIXABLE_INTENDED: On closer inspection, deviation is actually intended behavior
• UNFIXABLE_FLAKY: Deviation is intermittent or caused by replay environment factors
• GAVE_UP: Exhausted attempts without clear diagnosis

Include reasoning for each outcome.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Use-Tusk
• Source: Use-Tusk/tusk-skills
• License: Apache-2.0

Install and usage instructions live in the source repository linked above.