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aws-lambda-best-practices

AWS Lambda best practices for function design, configuration, and operations. Use when designing Lambda functions, choosing memory/timeout settings, planning concurrency and scaling, setting up monitoring, processing streams, or securing Lambda workloads. Triggers on tasks involving Lambda function creation, handler design, cold start optimization, idempotency, event source mapping, reserved/provisioned concurrency, or deciding whether Lambda is the right compute choice. Does not cover language-specific SDK patterns, CloudFormation/Terraform resource definitions, or Lambda@Edge.

74

Quality

93%

Does it follow best practices?

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SecuritybySnyk

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SKILL.md
Quality
Evals
Security

Quality

Content

86%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-executed reference-style skill: lean tables, concrete thresholds and named tools, and a clean one-level-deep bundle split into real files. The main weaknesses are duplicated guidance across sections (including a redundant closing reference index) and the absence of an explicit sequenced workflow with validation checkpoints.

Suggestions

Remove the closing 'Reference Files' section (or the per-section 'See references/...' sentences) — they duplicate each other verbatim and cost tokens without adding navigation value.

Consolidate repeated guidance: idempotency, `ReportBatchItemFailures`, 'reserved concurrency = 0', and module-level client initialization each appear 2-3 times across sections; state each once in its canonical section and cross-reference briefly from the Common Mistakes table.

Add a short sequenced 'designing a new function' workflow with validation checkpoints (e.g., fit assessment → memory tuning via Power Tuning with load-test verification → timeout/concurrency sizing → alarm setup), which would also lift workflow clarity.

DimensionReasoningScore

Conciseness

The body is dense and assumes Claude's competence — no 'what is Lambda' padding, tables throughout, concrete numbers doing the work ('1,769 MB', '6x function timeout', 'p99 + 20-50% buffer'). It loses a point to redundancy: idempotency appears in three sections, `ReportBatchItemFailures` and 'reserved concurrency 0' each appear twice, and the closing 'Reference Files' section repeats the per-section 'See references/...' pointers verbatim.

4 / 5

Actionability

Although code-free (permitted for instruction-only skills), the guidance is fully concrete: exact thresholds ('IteratorAge > 30,000 ms', 'ConcurrentExecutions > 80% of reserved'), sizing formulas ('Concurrency = RPS x duration', 'peak x 1.3', 'SQS Visibility Timeout >= 6x function timeout'), named tools (Power Tuning, Powertools, EMF, RDS Proxy, SnapStart), and a Common Mistakes table where every mistake is paired with a specific fix.

5 / 5

Workflow Clarity

Decision processes are clear — the fit-assessment table, memory/CPU tiers, and concurrency-control selection table act as checkpoints for 'should I use Lambda / how much memory / which control'. But this is a topical reference rather than a sequenced procedure: there is no ordered first-function workflow (e.g., fit check → tune memory → set alarms → load test), and no validate-and-retry loops, though the lack of destructive batch operations means the workflow-clarity cap does not apply.

4 / 5

Progressive Disclosure

Verified against the actual bundle: all seven `references/*.md` files referenced in the body exist, each pointer is one level deep and states what the reference covers ('for batch tuning parameters, partial batch response implementation, Kinesis shard management, ...'), and cross-references between reference files are sibling-level, not nested chains. The body keeps only overview-level detail and pushes implementation depth to the references.

5 / 5

Total

18

/

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.

An exemplary description: third-person voice, concrete capability enumeration, two complementary trigger clauses, and explicit non-goals. It states exactly what the skill covers, when to reach for it, and where its boundaries are without padding.

DimensionReasoningScore

Specificity

The description enumerates multiple concrete capability areas — "function design, configuration, and operations", "choosing memory/timeout settings", "planning concurrency and scaling", "setting up monitoring, processing streams, or securing Lambda workloads" — with comprehensive coverage of the skill's scope, matching the level of the anchor-5 example. It is not merely generic ('best practices for AWS') but breaks the domain into specific operations.

5 / 5

Completeness

It explicitly answers both what ("AWS Lambda best practices for function design, configuration, and operations") and when, twice over: "Use when designing Lambda functions, choosing memory/timeout settings, ..." and "Triggers on tasks involving Lambda function creation, handler design, ...". It also adds explicit negative scope ("Does not cover language-specific SDK patterns, CloudFormation/Terraform resource definitions, or Lambda@Edge"), exceeding the anchor-5 example.

5 / 5

Trigger Term Quality

Natural terms a user would say are comprehensively covered: "Lambda", "Lambda functions", "memory/timeout settings", "concurrency", "cold start optimization", "idempotency", "event source mapping", "handler design". Both the everyday phrasings and the practitioner-jargon triggers are present, matching the comprehensive-coverage anchor.

5 / 5

Distinctiveness Conflict Risk

The niche is unambiguous (AWS Lambda operations and design), and the explicit exclusions of SDK patterns, IaC definitions, and Lambda@Edge sharply reduce overlap with adjacent AWS skills — a clear niche with distinct triggers and minimal conflict risk.

5 / 5

Total

20

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository

provectus/awos-recruitment

Path

registry/skills/aws-lambda-best-practices/SKILL.md

Reviewed

Table of Contents

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