controlling-costs

Analyzes Axiom query patterns to find unused data, then builds dashboards and monitors for cost optimization. Use when asked to reduce Axiom costs, find unused columns or field values, identify data waste, or track ingest spend.

Quality

83%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Quality

Content

78%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-organized, highly actionable body with clear phased workflows and real validation checkpoints. Its main weakness is progressive disclosure: several referenced reference/template files are absent from the bundle, breaking the navigation the body promises.

Suggestions

Add the missing referenced files (reference/dashboard-panels.md, reference/monitor-strategy.md, reference/analysis-report-template.md, templates/dashboard.json) to the bundle, or inline the essential parts into SKILL.md so the detail is actually reachable.

Add an explicit validation/confirmation checkpoint before finalizing destructive DROP/SAMPLE recommendations in Phase 4 (e.g. 'present recommendations and confirm with the user before any DROP action').

Fix the reference path consistency — the body uses 'reference/' (singular) while the convention is 'references/'; align the paths with the actual bundle layout.

Dimension	Reasoning	Score
Conciseness	The body is largely lean — tables, concrete commands, and minimal prose — and avoids explaining concepts Claude already knows; a few descriptive lines (e.g. monitor rationale, the Tips block) could be trimmed, keeping it just below the 'every token earns its place' anchor.	4 / 5
Actionability	Provides copy-paste-ready bash commands with real flags (e.g. 'scripts/baseline-stats -d <deployment> -a <audit-dataset>'), complete APL queries, and a substitution instruction for placeholders, covering the common cases across all phases.	5 / 5
Workflow Clarity	Clear phase sequence with a routing table, preflight verification (audit dataset, axiom-history access, contract gate), decision branches (If 0 queries -> recommend DROP), and a 'Done when' checklist; the minor gap is no explicit confirm-with-user checkpoint before finalizing destructive DROP/SAMPLE recommendations.	4 / 5
Progressive Disclosure	Structure and signaling are sound — detail is pushed to one-level-deep references ('See reference/dashboard-panels.md for details') — but the referenced files (reference/dashboard-panels.md, reference/monitor-strategy.md, reference/analysis-report-template.md, templates/dashboard.json) do not exist in the bundle, so the disclosure path is broken and the detail is unreachable.	3 / 5
	Total	16 / 20 Passed

Description

87%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, third-person description that states concrete capabilities and pairs them with an explicit, naturally-phrased 'Use when' trigger clause scoped to the Axiom cost niche. Minor specificity gains would come from naming the optimization/recommendation actions directly.

Dimension	Reasoning	Score
Specificity	Lists several concrete actions — 'Analyzes Axiom query patterns to find unused data', 'builds dashboards and monitors' — tied to a specific domain; minor gap is that the dataset-level optimization actions (DROP/SAMPLE) are folded into a purpose clause rather than stated as actions.	4 / 5
Completeness	Explicitly answers both what ('Analyzes Axiom query patterns... builds dashboards and monitors') and when with a concrete 'Use when asked to reduce Axiom costs, find unused columns...' trigger clause, matching the anchor for clear what + concrete triggers.	5 / 5
Trigger Term Quality	The 'Use when' clause supplies natural phrases users would say — 'reduce Axiom costs', 'find unused columns or field values', 'identify data waste', 'track ingest spend' — with good coverage but a few synonyms (e.g. 'optimize spending', 'cut Axiom bill') absent.	4 / 5
Distinctiveness Conflict Risk	Scoped tightly to the Axiom cost-control niche with platform-specific triggers ('Axiom costs', 'ingest spend'), giving it a clear niche with minimal conflict risk against generic dashboard or SRE skills.	5 / 5
	Total	18 / 20 Passed

Validation

100%

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: openclaw/clawhub
Path: .agents/skills/controlling-costs/SKILL.md
Commit: 694ff71

Reviewed: 1 day ago

Table of Contents

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