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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.

Quality

85%

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Overview
Quality
Evals
Security
Files

Quality

Content

71%Weight 40%Scale 1-5

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

Well-structured content with an exemplary progressive-disclosure split — a decision-surface SKILL.md over one verified one-level-deep code reference — and a clearly sequenced workflow with explicit drift-validation. The main cost is redundancy: the Unity/Unreal determinism contract and the same Unity API URL are repeated many times, inflating token cost without adding information.

Suggestions

State the input-level (Unity/Godot) vs replication-stream (Unreal) determinism contract once — in the Step 2 table — and have the Limitations and Anti-patterns entries reference it instead of restating it in full.

Cite the Unity InputEventTrace API URL once (e.g., in References or the Overview table) and use short text mentions elsewhere; three consecutive anti-pattern rows currently repeat the full URL.

Add an explicit Step 1 exit checkpoint (e.g., replay a short session twice and compare state hashes) so users verify determinism is locked before recording the real session.

DimensionReasoningScore

Conciseness

The body is dense and tabular with no explanations of concepts Claude already knows, but the input-level-vs-replication-stream determinism split is restated in at least four places (Step 2 table, the 'key split' paragraph, Limitations, Anti-patterns), and the same Unity InputEventTrace API URL is repeated in full roughly six times, including three consecutive anti-pattern rows. This is more than the 'minor instances that could be trimmed' of the 4 anchor, though the prose itself is not padded enough for the 2 anchor.

3 / 5

Actionability

Concrete, specific guidance throughout — exact console commands (DemoRec/DemoPlay/DemoStop), flags (recordFrameMarkers = true), storage paths, buffer sizing, assertion models, and a fully worked Unity example — with the executable code itself delegated to references/engine-record-replay-apis.md, which exists and contains complete record/replay/CI code for all three engines. It stops short of the 5 anchor only because the body itself carries no executable code, routing it to the reference instead.

4 / 5

Workflow Clarity

A clear four-step sequence (lock determinism → pick capture level and record/replay → wire CI assertions → fail-safe for drift) with explicit validation: the CI hash-compare loop ('Mismatch → CI fails the build') and Step 4's protocol distinguishing bug-in-build from replay-stale with defined re-record/fail branches, plus an Inputs checklist to gather up front. It misses the 5 anchor on one gap: no checkpoint verifying determinism is actually achieved (e.g., double-replay compare) before committing to a recording.

4 / 5

Progressive Disclosure

The body is exactly the advertised 'cross-engine decision surface': overview, when/how to use, inputs, workflow, worked example, anti-patterns, and limitations, with all per-engine code split into a single one-level-deep reference that is clearly signaled at each point of use ('full working record + replay code in references/engine-record-replay-apis.md'). The reference file exists and does not nest further references, matching the top anchor.

5 / 5

Total

16

/

20

Passed

Description

92%Weight 40%Scale 1-5

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 strong description: concrete, engine-specific capabilities and an explicit 'Use when' clause with three well-differentiated trigger scenarios. The only weakness is that a few natural synonyms a user might say (playback, input trace, frame-perfect) are not covered, keeping trigger-term quality just below the top anchor.

DimensionReasoningScore

Specificity

The description enumerates 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 comprehensively names the per-engine API surfaces (InputEventTrace Enable/Disable/WriteTo/ReadFrom/Replay; DemoRec/DemoPlay/DemoStop plus DemoNetDriver + NetworkReplayStreamer; Godot deterministic-RNG + input-script). Nothing is vague or generic, matching the comprehensive-coverage anchor rather than the 'several specific actions with minor gaps' anchor.

5 / 5

Completeness

It explicitly answers both questions: what ('Build a deterministic gameplay record/replay test artefact for Unity, Unreal, or Godot — record... replay... assert that the resulting game state matches the original') and when ('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'), with concrete trigger phrases matching the 5 anchor.

5 / 5

Trigger Term Quality

Good natural-term coverage — 'replay', 'record a player session', 'regression-test artefact', 'bug repros', 'spectator / esports', 'netcode', plus all three engine names. It falls short of the 5 anchor because common variations users might say ('playback', 'input trace', 'frame-perfect', '.replay' files) are absent, but it is well above the 3 anchor's 'missing common variations' level.

4 / 5

Distinctiveness Conflict Risk

A clear niche (engine-specific deterministic gameplay record/replay) with distinct triggers tied to named engines and APIs; minimal realistic overlap with any neighboring skill, matching the clear-niche anchor.

5 / 5

Total

19

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

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