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testland/gameplay-recording-replay

Build a deterministic gameplay record/replay test artefact for Unity, Unreal, or Godot - record a player session, save it to disk, replay it bit-for-bit, and assert that the resulting game state matches the original. Covers Unity Input System's InputEventTrace API (Enable / Disable / WriteTo / ReadFrom / Replay) for input-level capture, Unreal's Replay System (DemoRec / DemoPlay / DemoStop console commands plus DemoNetDriver + NetworkReplayStreamer, default storage at %LOCALAPPDATA%/{Project}/Saved/Demos) for replication-stream capture, and Godot's community-pattern deterministic-RNG + input-script replay since Godot ships no first-party replay system. Use when authoring a regression-test artefact for player-recorded sessions, building a netcode replay for spectator / esports, or producing reproducible bug repros for cert teams.

79

Quality

99%

Does it follow best practices?

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Overview
Quality
Evals
Security
Files

Quality

Content

100%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-architected multi-engine skill: a lean cross-engine decision surface with a sequenced Step 1-4 workflow, explicit validation and replay-drift feedback loops, concrete commands and API surfaces inline, and full executable code correctly deferred to a single one-level-deep reference file. Quality is strong across all dimensions with no notable weaknesses.

DimensionReasoningScore

Conciseness

The body assumes Claude's competence (no basic concept primers on what Unity/Godot or a replay is), defers full code to the reference file, and keeps each section information-dense. The recurring Unity-vs-Unreal determinism restatement is purposeful emphasis of the core distinction, not padding.

3 / 3

Actionability

Inline guidance is concrete and executable: exact console commands (DemoRec/DemoPlay/DemoStop with GEngine->Exec), specific API method sequences, concrete storage paths, buffer sizes (4 MB / 64 MB), a SHA-256 of GameStateRoot.Serialize() assertion model, and a fully specified worked example with committed baseline/hash paths.

3 / 3

Workflow Clarity

A clear Step 1-4 sequence with explicit validation checkpoints: Step 1 locks determinism as a prerequisite, Step 3's CI loop ends with 'Mismatch -> CI fails the build', and Step 4 defines a feedback loop distinguishing bug-in-build from replay-stale via replay_format/build_hash header checks.

3 / 3

Progressive Disclosure

SKILL.md is an overview/decision surface with one clearly signaled, one-level-deep reference (references/engine-record-replay-apis.md, verified present) that holds the full per-engine code; the reference does not chain further, and content is appropriately split between decision surface and implementation detail.

3 / 3

Total

12

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12

Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A dense, highly specific description that names concrete per-engine APIs and includes an explicit 'Use when...' trigger clause covering regression tests, spectator/esports replays, and cert bug repros. It is borderline verbose but every detail reinforces specificity rather than padding.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ('record a player session, save it to disk, replay it bit-for-bit, and assert that the resulting game state matches the original') and names exact engine APIs (InputEventTrace Enable/Disable/WriteTo/ReadFrom/Replay; DemoRec/DemoPlay/DemoStop; DemoNetDriver + NetworkReplayStreamer).

3 / 3

Completeness

Explicitly answers both what (build/record/save/replay/assert across three engines) and when via a present 'Use when...' clause with three distinct triggers, so no 2-cap applies.

3 / 3

Trigger Term Quality

The 'Use when...' clause surfaces natural user terms ('regression-test artefact for player-recorded sessions', 'netcode replay for spectator / esports', 'reproducible bug repros for cert teams'), reinforced by the keywords metadata field covering 'replay, recording, input-trace, demonet, deterministic'.

3 / 3

Distinctiveness Conflict Risk

The gameplay record/replay niche for Unity/Unreal/Godot is narrow with engine-specific triggers unlikely to collide with general testing skills.

3 / 3

Total

12

/

12

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Reviewed

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