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testland/libfaketime-c

Wraps libfaketime (github.com/wolfcw/libfaketime), the LD_PRELOAD library that fakes the clock for any binary by intercepting time() / gettimeofday() / clock_gettime(). Covers absolute-date mode (FAKETIME='2026-12-31 23:59:00'), relative offset (FAKETIME='-1d'), advance-rate (FAKETIME='@2026-12-31 23:59:00 x5' for 5x speed), per-process scope via LD_PRELOAD, and FAKETIME_NO_CACHE for high-resolution mocking. Use when you need to fake time, mock the clock, or freeze time for C/C++ or any native binary that needs deterministic wall-clock time.

76

Quality

96%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

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SecuritybySnyk

Medium

Suggest reviewing before use

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-organized, actionable skill body that assumes competence, leads with executable commands, sequences the workflow with verification, and cleanly offloads detail to a single real reference file.

DimensionReasoningScore

Conciseness

The body is lean, assumes Claude's competence (no generic explanations of what a clock or library is), and every section earns its place; the minor overlap between the 'How to use' steps and the 'Authoring' section is structural rather than padded fluff.

3 / 3

Actionability

Provides copy-paste-ready, fully executable guidance throughout — install commands, the faketime wrapper invocation, raw LD_PRELOAD, a Python subprocess test, and a CI yaml snippet — matching the anchor-3 example.

3 / 3

Workflow Clarity

The 7-step 'How to use' is clearly sequenced with an explicit verification step (step 6: assert on visible output), and the worked example adds a 4-step DST sequence; this is not a destructive/batch operation, so no feedback-loop cap applies.

3 / 3

Progressive Disclosure

SKILL.md is a concise overview that offloads variant syntax and recipes to one real, clearly-signaled, one-level-deep reference (references/faketime-modes-and-recipes.md, verified present), matching the anchor-3 pattern.

3 / 3

Total

12

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12

Passed

Description

90%

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, specific description with explicit triggers and a clear technical niche. The only weakness is the second-person 'you' phrasing, which violates the rubric's third-person voice rule and costs one specificity point.

Suggestions

Rewrite the trigger clause in third person to avoid the voice penalty, e.g. 'Use when faking time, mocking the clock, or freezing time for C/C++ or any native binary that needs deterministic wall-clock time.'

Keep the concrete syscall/mode enumeration as-is — it is the strongest part of the description for specificity.

DimensionReasoningScore

Specificity

Lists multiple concrete actions and modes ('intercepting time() / gettimeofday() / clock_gettime()', absolute-date, relative offset, advance-rate, FAKETIME_NO_CACHE), matching the anchor-3 example, but the second-person phrasing 'Use when you need to...' triggers the rubric's -1 specificity penalty for non-third-person voice.

2 / 3

Completeness

Explicitly answers both what ('the LD_PRELOAD library that fakes the clock...') and when ('Use when you need to fake time... for C/C++ or any native binary...'), matching the anchor-3 example with an explicit trigger clause.

3 / 3

Trigger Term Quality

Includes natural user phrases 'fake time, mock the clock, or freeze time' plus 'deterministic wall-clock time', giving good coverage of terms a user would actually say.

3 / 3

Distinctiveness Conflict Risk

The LD_PRELOAD / native-binary scoping ('for C/C++ or any native binary') carves a clear niche distinct from language-native fake-timer siblings, making wrong-skill triggering unlikely.

3 / 3

Total

11

/

12

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Reviewed

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