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/compare-cache-runs

Compares two `tuist cache` runs to identify cache hit rate changes and root-cause analysis of cache invalidation. Can be invoked with cache run IDs, dashboard URLs, or branch names.

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$ npx -y skills add tuist/tuist --skill compare-cache-runs --agent claude-code

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How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/compare-cache-runs

Context preview

The summary Claude sees to decide when to auto-load this skill.

Compares two `tuist cache` runs to identify cache hit rate changes and root-cause analysis of cache invalidation. Can be invoked with cache run IDs, dashboard URLs, or branch names.

SKILL.md

compare-cache-runs.SKILL.md
name: compare-cache-runs
description: Compares two `tuist cache` runs to identify cache hit rate changes and root-cause analysis of cache invalidation. Can be invoked with cache run IDs, dashboard URLs, or branch names.

Compare Cache Runs

Quick Start

You'll typically receive two cache run identifiers. Follow these steps:

1. Run `tuist cache-run list --json` to find cache runs on each branch. 2. Run `tuist cache-run show <id> --json` for both base and head cache runs. 3. Compare duration, status, and cache hit rates. 4. Summarize cache changes with root cause analysis.

Step 1: Resolve Cache Runs

If base/head are cache run IDs or dashboard URLs

Fetch each directly:

tuist cache-run show <base-id> --json
tuist cache-run show <head-id> --json

If base/head are branch names

List recent cache runs on each branch:

tuist cache-run list --git-branch <base-branch> --json --page-size 1
tuist cache-run list --git-branch <head-branch> --json --page-size 1

Then fetch full details with `tuist cache-run show <id> --json`.

Defaults

  • If no base is provided, use the project's default branch (usually `main`).
  • If no head is provided, detect the current git branch.

Step 2: Compare Top-Level Metrics

After fetching both cache runs, compare:

| Metric | What to check | |---|---| | `duration` | Flag if head is >10% slower | | `status` | Flag if base succeeded but head failed | | `cacheable_targets` | Note if target count changed | | `local_cache_target_hits` | Compare local hit counts | | `remote_cache_target_hits` | Compare remote hit counts | | `is_ci` | Note if one is CI and the other local |

Compute cache hit rates:

  • Base: `(local_hits + remote_hits) / cacheable_targets * 100`
  • Head: same formula
  • Delta: `head_rate - base_rate`

Step 3: Analyze Cache Invalidation

If cache hit rate dropped, the key question is: **which target(s) caused the invalidation cascade?**

Cache invalidation in `tuist cache` works the same way as in `tuist generate`: 1. A "root cause" target has a direct change (source file modified, build setting changed, etc.) 2. All targets that depend on the root cause target also get invalidated because their `dependencies` hash changes. 3. This cascade can invalidate many targets from a single root change.

Identifying root cause targets

Without the module cache target detail endpoint (available via MCP), use these heuristics:

1. Check `git diff` between the base and head commits to see which files changed. 2. Map changed files to their Tuist targets/modules. 3. Targets with direct source changes are likely root causes. 4. Targets that only changed due to dependency hash cascading are secondary invalidations.

Common root causes of cache invalidation

| Cause | Description | |---|---| | Source changes | Files in the target's source directory were modified | | Resource changes | Assets, XIBs, storyboards, or other resources changed | | Build settings | Target or project build settings were modified | | Dependency changes | An external dependency version changed | | Info.plist changes | The target's Info.plist was modified | | Entitlements changes | The entitlements file was modified | | Deployment target | The minimum deployment target changed | | Headers | Public or project headers changed | | Project settings | Shared project-level settings changed |

Step 4: Assess Impact

Categorize the cache invalidation:

  • **Expected**: Source files were intentionally changed, causing expected cache misses.
  • **Unexpected**: No source changes but cache was invalidated (build settings, Xcode version, etc.).
  • **Cascade**: A small change invalidated many downstream targets.

For `tuist cache` specifically, also consider:

  • Cache warming strategy: Was the cache run warming from scratch or incrementally?
  • The `command_arguments` field can reveal if different flags were used.

Summary Format

Produce a summary with:

1. **Overall verdict**: Cache hit rate improved, regressed, or stable. 2. **Cache hit rate**: Base rate vs head rate with delta. 3. **Duration**: Absolute and percentage change. 4. **Root cause targets**: Which targets had direct changes. 5. **Cascade impact**: How many targets were invalidated due to dependency cascading. 6. **Recommendations**: How to minimize cache invalidation.

Example:

Cache Run Comparison: base (run-123 on main) vs head (run-456 on feature-x)

Duration: 95.2s -> 142.8s (+50%) -- REGRESSION
Cache hit rate: 88% (44/50) -> 60% (30/50) (-28%) -- REGRESSION
Status: success -> success

Root cause: CoreModule had source changes (5 files modified).
This cascaded to 14 downstream targets that depend on CoreModule.

Cache invalidation breakdown:
- Direct changes: CoreModule (sources changed)
- Cascade: UIKit, Networking, Analytics, + 11 others (dependency hash changed)

Recommendations:
- Consider splitting CoreModule into smaller, more focused modules
- Use interface/implementation module pattern for frequently-changed modules
- Run `tuist cache` on the feature branch after rebasing to warm caches

Done Checklist

  • Resolved both base and head cache runs
  • Compared duration and cache hit rates
  • Identified root cause targets for cache invalidation
  • Analyzed cascade impact
  • Provided actionable recommendations for reducing cache misses
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