timestream-influxdb

Retrieves authoritative guidance on Amazon Timestream for InfluxDB (managed InfluxDB 2, InfluxDB 2 Read Replica Clusters, InfluxDB 3 Core and Enterprise). Applicable to any InfluxDB-on-AWS request including engine selection, provisioning (Marketplace + AmazonTimestreamInfluxDBFullAccess/ConsoleFullAccess IAM), schema design (tags vs fields, cardinality, HTTP/sensor/metric data modeling), migration from LiveAnalytics, Processing Engine plugins, connectivity (port 8086 V2, port 8181 V3, VPC-only by default), and write/query errors.

Quality

86%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

72%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A strong, operational body with executable CLI commands, concrete specifics (ports, plugins, metrics), and clean one-level-deep progressive disclosure. Its weaknesses are length that could be tightened and a missing post-provisioning verification step despite destructive mutations and an unused health_check.sh script.

Suggestions

Tighten verbose sections: condense the 'Advisory in nature' paragraph and the 5-step handoff protocol, and rely on a single authoritative port statement rather than restating 8086/8181 across multiple sections.

Wire verification into destructive workflows: after create-db-instance/create-db-cluster, instruct running scripts/health_check.sh (and reference scripts/get_token.sh, check_vpc_endpoints.sh where relevant) to add a validate→fix→retry feedback loop and lift workflow clarity.

Surface the existing scripts/ in the body — currently get_token.sh, health_check.sh, check_vpc_endpoints.sh, input_validator.py, and instance_types.py are never referenced, leaving actionable tooling undiscoverable.

Dimension	Reasoning	Score
Conciseness	The body is operational and assumes Claude's competence (it does not explain what InfluxDB or time-series DBs are), but at ~230 lines it is long and could be tightened — the 'Advisory in nature' paragraph, the 5-step handoff protocol, and repeated reinforcement of the 8086/8181 port facts across sections add length beyond the lean anchor.	2 / 3
Actionability	Provides copy-paste-ready executable commands ('aws timestream-influxdb list-db-instances --region us-east-1', the --maintenance-schedule JSON example, concrete --tags examples) plus specific decision flows, exact plugin names, and exact CloudWatch metric names — fully concrete guidance rather than vague direction.	3 / 3
Workflow Clarity	Common Tasks are clearly numbered 1–6 with pre-flight validation checklists ('You MUST confirm which engine...', 'verify aws CLI', the four MUST facts before provisioning), but destructive/provisioning operations lack an explicit post-action verification or validate→fix→retry feedback loop — notably a health_check.sh script exists in scripts/ yet is never wired into the workflow, capping this at 2 per the feedback-loop guidance for destructive changes.	2 / 3
Progressive Disclosure	The body is an overview that delegates detail to one-level-deep, clearly signaled references — every 'Load [X instructions](references/.../instructions.md)' and metrics.md link resolves to a real file under references/<topic>/, with content appropriately split and easy to navigate, matching the well-signaled one-level-deep anchor.	3 / 3
	Total	10 / 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 dense, specific, third-person description that clearly states what the skill covers and when to invoke it, with concrete ports, IAM policy names, and engine variants rather than vague language. It is comprehensive and well-triggered with minimal conflict risk.

Dimension	Reasoning	Score
Specificity	Enumerates multiple concrete capabilities — 'engine selection, provisioning (Marketplace + AmazonTimestreamInfluxDBFullAccess/ConsoleFullAccess IAM), schema design (tags vs fields, cardinality, HTTP/sensor/metric data modeling), migration from LiveAnalytics, Processing Engine plugins, connectivity (port 8086 V2, port 8181 V3, VPC-only by default)' — with specific port numbers and IAM policy names, matching the 'lists multiple specific concrete actions' anchor.	3 / 3
Completeness	Answers both what ('Retrieves authoritative guidance on Amazon Timestream for InfluxDB...') and when via equivalent explicit trigger guidance ('Applicable to any InfluxDB-on-AWS request including...'), satisfying the 'Use when' requirement; not capped at 2 because explicit trigger guidance is present.	3 / 3
Trigger Term Quality	Covers natural terms users would say — 'InfluxDB', 'Amazon Timestream for InfluxDB', 'InfluxDB on AWS', 'schema design', 'tags vs fields', 'migration from LiveAnalytics', 'Processing Engine', 'write/query errors' — good coverage of common variations rather than opaque jargon.	3 / 3
Distinctiveness Conflict Risk	Scoped to a narrow, specific niche — Amazon Timestream for InfluxDB with named engine variants and ports — with distinct triggers unlikely to fire for unrelated skills; the handoff section even scopes it relative to the aws-database-selection parent.	3 / 3
	Total	12 / 12 Passed

Validation

81%

Warnings & errors only

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

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning
relative_links	Relative link issues: 9 deeper-than-1-level	Warning
referenced_paths_exist	Referenced path issues: 11 deeper-than-1-level	Warning

	Total	13 / 16 Passed

Repository: aws/agent-toolkit-for-aws
Path: skills/specialized-skills/database-skills/timestream-influxdb/SKILL.md
Commit: 222ce56

Reviewed: 3 days ago

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