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testland/graphql-n-plus-one-remediation

Detects and fixes the GraphQL N+1 pattern: scans a repo, PR diff, or schema type for list-returning resolvers (grep-driven detection workflow), traces the resolver tree to locate the fan-out (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 reviewing a PR that adds or changes a list-returning resolver, 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.

75

Quality

94%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Overview
Quality
Evals
Security
Files

Quality

Content

92%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.

A well-structured, actionable skill body with executable code, an explicit validation step, and clean one-level-deep references. The only minor gap is occasional explanatory prose that could be trimmed for token efficiency.

DimensionReasoningScore

Conciseness

Largely lean and assumes Claude's competence — no padding about what GraphQL or libraries are — but sections like 'Observable symptoms' and 'Limitations' carry explanatory prose that could be tightened in places.

4 / 5

Actionability

Fully executable, copy-paste-ready TypeScript and bash for each fix (DataLoader, eager projection, selection-set prefetch) plus a call-count assertion test and Prisma query-log snippet covering the common cases.

5 / 5

Workflow Clarity

Steps 0–4 are clearly sequenced with an explicit validation checkpoint in Step 4 (assert call count, confirm via query log) and feedback loops ('Confirm against a query log... before filing it').

5 / 5

Progressive Disclosure

SKILL.md is a clear overview with two well-signaled one-level-deep references to real files (references/fixes.md, references/examples.md); detail is appropriately split out rather than inlined.

5 / 5

Total

19

/

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: it states concrete capabilities and gives explicit, scenario-based trigger guidance with minimal conflict risk. Trigger term quality is slightly below top because the triggers lean scenario-based rather than covering natural synonyms a user would say verbatim.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — scans repo/PR diff/schema type for list-returning resolvers, traces the resolver tree to locate fan-out, classifies child resolvers as safe or N+1 risk, and applies one of three named fixes — giving comprehensive coverage.

5 / 5

Completeness

Explicitly answers both what (detects and fixes the N+1 pattern via a grep-driven detection and classification workflow) and when ('Use when reviewing a PR..., when a connection-pool exhaustion... traces back to GraphQL traffic, or when a resolver trace shows...').

5 / 5

Trigger Term Quality

Includes scenario-based triggers ('reviewing a PR that adds or changes a list-returning resolver', 'connection-pool exhaustion or slow-query alert', 'resolver trace shows a child field resolved once per parent row') plus 'GraphQL N+1', but lacks common natural-language synonym variations a user would say verbatim.

4 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (GraphQL N+1 remediation) with distinct, specific triggers that would not match unrelated skills, giving minimal conflict risk.

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Reviewed

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