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sre-engineer

Defines service level objectives, creates error budget policies, designs incident response procedures, develops capacity models, and produces monitoring configurations and automation scripts for production systems. Use when defining SLIs/SLOs, managing error budgets, building reliable systems at scale, incident management, chaos engineering, toil reduction, or capacity planning.

71

Quality

89%

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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-structured, highly actionable skill body: dense executable examples, a gated workflow sequence, and an exemplary load-when reference table pointing to real one-level-deep bundle files. The main improvement opportunity is trimming the longest inline code blocks into the references and adding a validation-failure feedback loop to the workflow.

DimensionReasoningScore

Conciseness

The body is dense and free of concept over-explanation — no prose padding, just workflow, constraints, and executable examples. It is not anchor 5 because the full ~35-line Python auto-remediation script and ~40-line Prometheus YAML inline in SKILL.md could be trimmed or moved to the references (which already cover equivalent depth), making a leaner overview. It exceeds anchor 3, whose 'unnecessary explanation' it does not contain.

4 / 5

Actionability

The examples are fully executable and copy-paste ready: a correct multiwindow burn-rate Prometheus alerting rule with realistic thresholds (0.014400 for 14.4x burn), working PromQL for all four golden signals, and a complete Python script with argument handling and error handling. These cover the most common SRE output cases, matching anchor 5's 'copy-paste ready code covering common cases'.

5 / 5

Workflow Clarity

The six-step Core Workflow is clearly sequenced and includes explicit gating checkpoints ('Confirm SLO targets reflect user expectations before proceeding', 'verify recovery meets RTO/RPO targets before marking the experiment complete'). It falls short of anchor 5 because there are no feedback loops describing what to do when a checkpoint fails (validate -> fix -> retry), which anchor 5 requires.

4 / 5

Progressive Disclosure

The Topic/Reference/Load-When table cleanly signals five one-level-deep references, all of which exist on disk and contain no nested references; the body keeps the overview plus key executable examples while the references hold the deeper guidance. This matches anchor 5's 'clear overview with well-signaled one-level-deep references; content appropriately split'.

5 / 5

Total

18

/

20

Passed

Description

88%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 pairs a concrete, third-person 'what' statement with an explicit 'Use when' trigger clause covering the main SRE use cases. The only weaknesses are a few missing natural trigger synonyms and slight overlap risk with adjacent devops/monitoring skills.

DimensionReasoningScore

Specificity

The description lists five concrete third-person actions tied to specific artifacts ('Defines service level objectives, creates error budget policies, designs incident response procedures, develops capacity models, and produces monitoring configurations and automation scripts'), giving comprehensive coverage of the SRE domain with no gaps — matching the anchor-5 example's breadth. It is not anchor 4, which is reserved for descriptions with minor coverage gaps.

5 / 5

Completeness

The first sentence explicitly answers 'what' with concrete capabilities and the second sentence provides an explicit 'Use when...' clause with concrete trigger phrases ('defining SLIs/SLOs, managing error budgets, ... chaos engineering, toil reduction, or capacity planning'), matching the anchor-5 example structure exactly. Not anchor 4, since the 'when' clause is already explicit and specific rather than needing more detail.

5 / 5

Trigger Term Quality

'SLIs/SLOs', 'error budgets', 'chaos engineering', 'toil reduction', and 'capacity planning' are phrases users would naturally say, but common variations like 'site reliability', 'on-call', 'postmortems', and 'MTTR' appear only in metadata.triggers rather than the description itself. Good keyword coverage with a few natural terms missing fits anchor 4; it falls short of anchor 5's comprehensive synonym coverage.

4 / 5

Distinctiveness Conflict Risk

Core SRE triggers (error budgets, chaos engineering, toil reduction) are highly distinct, but 'produces monitoring configurations' and 'building reliable systems at scale' carry minor overlap with closely related devops, monitoring, and architecture skills — the metadata itself lists devops-engineer and cloud-architect as related. This is 'mostly distinct; minor overlap risk with closely related skills' (anchor 4) rather than the minimal-conflict profile of anchor 5.

4 / 5

Total

18

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

Jeffallan/claude-skills

Path

skills/sre-engineer/SKILL.md

Reviewed

Table of Contents

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