cost-spike-investigation

Use when a cost spike or unexpected increase has already been identified and you need to find which service, account, or resource is responsible

Quality

57%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Fix and improve this skill with Tessl

tessl review fix ./plugins/cost-analyst/skills/cost-spike-investigation/SKILL.md

Quality

Content

57%

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

This is a reasonably well-structured investigative skill with a clear 7-step workflow and good progressive disclosure to supporting references. Its main weaknesses are verbosity (explaining concepts Claude already knows, like common spike patterns and generic best practices) and the pseudo-code nature of the examples which aren't truly executable. Adding validation checkpoints and error-handling within the workflow steps would strengthen it significantly.

Suggestions

Remove or significantly trim the 'Common Spike Patterns' section and generic best practices ('compare apples to apples', 'be specific') — Claude already knows these patterns and the advice is not actionable.

Add validation checkpoints within the workflow, e.g., 'If no single service accounts for >20% of the increase, broaden to multi-dimensional analysis' or 'If query returns empty results, check date range validity and available dimensions.'

Make code examples more concrete by showing actual tool call syntax (MCP tool names, exact parameter formats) rather than abstract function signatures with placeholder arguments.

Dimension	Reasoning	Score
Conciseness	The skill includes some unnecessary sections like 'When to Use' with obvious keywords, 'Common Spike Patterns' that Claude already knows, and the 'Purpose' section restates what the description already covers. The 'Best Practices' list contains generic advice ('compare apples to apples', 'be specific'). However, the core workflow steps are reasonably efficient.	2 / 3
Actionability	The code examples use plausible function signatures with clear parameters, but they are pseudocode-style calls to undefined functions (get_cost_data, get_dimension_values) rather than actual executable API calls or tool invocations. The placeholders like '<spike_period>' reduce copy-paste readiness. The output format section is well-structured but the investigation steps lack concrete expected response handling.	2 / 3
Workflow Clarity	The 7-step workflow is clearly sequenced and logically progresses from broad to narrow investigation. However, there are no explicit validation checkpoints or feedback loops — no guidance on what to do if a query returns no data, if the spike doesn't appear in any dimension, or how to verify findings before reporting. For an investigative workflow that could lead to incorrect conclusions, this is a gap.	2 / 3
Progressive Disclosure	The skill provides a clear overview with well-signaled references to external files (best-practices.md, cloudzero-tools-reference.md, error-handling.md, dimensions-reference.md, cost-types-reference.md). References are one level deep and clearly organized in a 'See Also' section. The prerequisite skill dependency is clearly stated.	3 / 3
	Total	9 / 12 Passed

Description

57%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description excels at defining when to use the skill (post-spike attribution) and is distinctive in its niche, but it lacks specificity about what concrete actions the skill performs. It reads more like a trigger clause than a full skill description, leaving the 'what does this do' question largely unanswered.

Suggestions

Add concrete capability descriptions before the 'Use when' clause, e.g., 'Analyzes cloud billing data to drill down into cost breakdowns by service, account, region, and resource. Compares spending across time periods to isolate root causes of cost increases.'

Include additional natural trigger terms users might say, such as 'billing spike', 'cloud spend', 'AWS/Azure/GCP costs', 'budget overrun', 'cost anomaly', or 'unexpected charges'.

Dimension	Reasoning	Score
Specificity	The description names the domain (cost spike investigation) and mentions some actions (finding which service, account, or resource is responsible), but doesn't list concrete actions like 'query cost explorer', 'compare billing periods', or 'generate breakdown reports'.	2 / 3
Completeness	The 'when' is well-defined ('when a cost spike or unexpected increase has already been identified'), but the 'what' is weak — it only says 'find which service, account, or resource is responsible' without describing the concrete methods or outputs. The description is essentially all trigger guidance with minimal capability description.	2 / 3
Trigger Term Quality	Includes relevant terms like 'cost spike', 'unexpected increase', 'service', 'account', 'resource', but misses common variations users might say such as 'billing', 'charges', 'AWS costs', 'cloud spend', 'budget overrun', or 'cost anomaly'.	2 / 3
Distinctiveness Conflict Risk	The description carves out a clear niche: post-identification cost spike attribution. The qualifier 'already been identified' distinguishes it from cost monitoring or anomaly detection skills, making it unlikely to conflict with other skills.	3 / 3
	Total	9 / 12 Passed

Validation

90%

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 — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	10 / 11 Passed

Repository: Cloudzero/cloudzero-claude-marketplace
Commit: 760a9c7

Reviewed: about 2 months ago

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