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testland/graphql-n-plus-one-remediation

Traces a GraphQL resolver tree to locate the N+1 pattern (one parent query returns N rows, then a child field resolver fires once per row), classifies every child field resolver as safe or N+1 risk, and applies one of three fixes: per-request DataLoader batching, eager projection in the parent resolver, or selection-set-aware prefetch. Use when a list-returning resolver is added or changed in review, when a connection-pool exhaustion or slow-query alert traces back to GraphQL traffic, or when a resolver trace shows a child field resolved once per parent row.

80

Quality

100%

Does it follow best practices?

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SecuritybySnyk

Passed

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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-structured remediation skill with executable code for every fix, a sequenced workflow ending in an explicit validation checkpoint, and clean one-level-deep references that were verified on disk. It is concise and action-oriented throughout.

DimensionReasoningScore

Conciseness

Lean body that frames only the resolver-tree mechanics specific to this skill rather than generic GraphQL concepts, and is dense with classification tables and executable code. Every section earns its place; not 2 because there is no padded explanation Claude would already know.

3 / 3

Actionability

Provides fully executable TypeScript for all three fixes (DataLoader, eager projection, selection-set-aware prefetch) plus a concrete jest call-count test and Prisma logging config. Examples are copy-paste ready, matching the anchor.

3 / 3

Workflow Clarity

Steps 1–4 are clearly sequenced with Step 4 an explicit validation checkpoint (call-count assertion) and a DB-layer query-log feedback loop. The classification table functions as a checklist, hitting the anchor for explicit validation steps.

3 / 3

Progressive Disclosure

SKILL.md is the overview; deep detail (batch-function contracts, per-request scoping failure, cartesian explosion) lives in references/fixes.md and worked examples in references/examples.md — both verified to exist, one level deep, and clearly signaled with markdown links.

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 strong, specific description that states concrete capabilities, gives explicit 'Use when' triggers using natural terms, and occupies a clear niche. It assumes no first/second-person voice and avoids fluff.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Traces a GraphQL resolver tree to locate the N+1 pattern', 'classifies every child field resolver as safe or N+1 risk', and 'applies one of three fixes: per-request DataLoader batching, eager projection... or selection-set-aware prefetch'. This exceeds the anchor for naming the domain and some actions.

3 / 3

Completeness

Clearly answers both what (trace, classify, fix) and when via an explicit 'Use when...' clause with three concrete trigger conditions. Not 2 because the trigger guidance is explicit rather than implied.

3 / 3

Trigger Term Quality

Natural practitioner terms a user would actually say are well covered: 'list-returning resolver', 'connection-pool exhaustion', 'slow-query alert', 'GraphQL traffic', and 'resolver trace shows a child field resolved once per parent row'.

3 / 3

Distinctiveness Conflict Risk

The GraphQL N+1 remediation niche is narrow with distinct triggers unlikely to collide with other skills. Third-person voice ('Traces', 'classifies', 'applies') incurs no voice penalty.

3 / 3

Total

12

/

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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