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send-experiment-designer

Use when the user asks to "design an email A/B test", "set up a multivariate subject/CTA test", "run a send-time test", "build a hold-out group", or "is this email result statistically and practically material?"; produces a falsifiable hypothesis, one-variable-per-cell matrix, sample-size/MDE/duration/power plan, and an effect/uncertainty read from own ESP data. Applies only a precommitted owner-approved action rule; the helper never chooses a business action. Not for EQS/vetoes or writing the email. 邮件AB测试设计/多变量测试/发送时间测试/留出组/显著性判定

Quality

86%

Does it follow best practices?

Run evals on this skill

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

70%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.

This is a strong, expert-level instruction body: an unambiguous mode-selection table, a fully sequenced nine-step workflow with genuine statistical and governance guardrails, concrete commands and numbers, and explicit failure paths (NEEDS_INPUT, UNDECIDED, underpowered fallbacks). Its weaknesses are systematic internal repetition that inflates token cost, and a reference architecture that reaches outside its own bundle through multi-level cross-skill paths that cannot be verified from the skill as shipped.

Suggestions

Define the four modes once — keep the opening table and reduce step 3's mode bullets to only the binding/contract specifics not already stated in the table.

State the next-skill routing and the never-authorizes-a-send boundary once each (Next Best Skill and the scope guard respectively) instead of repeating them across the Skill Contract, Instructions, and Termination sections.

Ship the shared references inside the skill's own references/ directory (or summarize their operative rules inline) so the skill is self-contained when the surrounding repo layout is absent, and document the argument format for the `samplesize` and `continuous` subcommands.

DimensionReasoningScore

Conciseness

The body is dense and domain-specific, but the same content is repeated: the four modes are fully defined in the opening table and again in step 3's mode-specific bullets; the email-quality-auditor handoff is stated in the scope guard, the Skill Contract, and the Next Best Skill section; the never-authorizes-a-send boundary and the NEEDS_INPUT condition each appear three-plus times. Fits anchor 3 ("mostly efficient but could be tightened") rather than 4 because the duplication is systematic, not isolated; not 2 because there is no explanation of concepts Claude already knows and the domain policy content earns its tokens.

3 / 5

Actionability

Gives a copy-paste-ready keyless command ("python3 "${CLAUDE_PLUGIN_ROOT}/scripts/connectors/experiment.py" proportion --control <events> <n> --variant <events> <n> --alpha <alpha> --min-lift <relative-bar>"), a fill-in hypothesis template, a numeric sample-size table, and an explicit duration formula. Not 5: the `samplesize` and `continuous` subcommands are named without argument formats, and the referenced script cannot be verified in this bundle; not 3: the primary workflows are fully executable with concrete numbers.

4 / 5

Workflow Clarity

Nine numbered steps in a clear design→read-out sequence with explicit validation gates: stop-and-return NEEDS_INPUT when inputs are missing, the no-peeking rule fixing sample and read date at design time, the ordered underpowered fallback ladder in step 6 (widen MDE → run longer → fewer cells → don't test), receipt/hash binding before calculating, and the UNDECIDED decision rule absent a precommitted owner-approved rule. Not 4: checkpoints are explicit and include error-recovery paths, not implicit.

5 / 5

Progressive Disclosure

Sections are well-organized and references are clearly signaled in a Reference Materials list with one-line descriptions, but no bundle files exist in this skill directory while the body depends on ~10 files reached via multi-level relative paths into shared repo space and other skills' bundles ("../../../references/skill-contract.md", "../../nurture/email-sequence-designer/references/send-control.md", "../../../influencer/report/roi-calculator/SKILL.md"), none verifiable here. Fits anchor 3 (structure present, organization could be better) rather than 4 because the skill's discoverability depends on an external repo layout with cross-skill hops rather than a one-level-deep local bundle.

3 / 5

Total

15

/

20

Passed

Description

100%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.

The description is a model example: concrete trigger phrases in the user's own words, a precise statement of what the skill produces, third-person voice, and explicit out-of-scope boundaries. Its only cost is length — it is dense and the trailing bilingual keyword block adds tokens — but every clause is functional rather than padded.

DimensionReasoningScore

Specificity

Lists multiple concrete outputs — "produces a falsifiable hypothesis, one-variable-per-cell matrix, sample-size/MDE/duration/power plan, and an effect/uncertainty read from own ESP data" plus "Applies only a precommitted owner-approved action rule" — comprehensive and specific to this domain. Not 4: coverage of the skill's actions is complete rather than having minor gaps; not below since nothing is generic.

5 / 5

Completeness

Explicitly answers both: what ("produces a falsifiable hypothesis, one-variable-per-cell matrix, sample-size/MDE/duration/power plan, and an effect/uncertainty read") and when ("Use when the user asks to..." with concrete trigger phrases), and also states what it will not do ("Not for EQS/vetoes or writing the email"). Not 4: both what and when are explicit with concrete triggers, not merely present.

5 / 5

Trigger Term Quality

Five verbatim natural trigger phrases ("design an email A/B test", "set up a multivariate subject/CTA test", "run a send-time test", "build a hold-out group", "is this email result statistically and practically material?") plus bilingual keyword synonyms cover the ways users actually ask for this. Not 4: synonym coverage (multivariate, send-time, hold-out, significance/materiality) is comprehensive rather than missing common variants.

5 / 5

Distinctiveness Conflict Risk

Clear niche (email experiment design/significance read) with distinct triggers and explicit negative boundaries — "Not for EQS/vetoes or writing the email" — that separate it from sibling email-quality and creative-writing skills. Not 4: the explicit exclusion clause plus domain-specific triggers give minimal conflict risk.

5 / 5

Total

20

/

20

Passed

Validation

81%

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

Validation — 13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

relative_links

Relative link issues: 17 suspicious

Warning

Total

13

/

16

Passed

Repository

aaron-he-zhu/aaron-marketing-skills

Path

email/deliver/send-experiment-designer/SKILL.md

Reviewed

Table of Contents

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