doctor

System health diagnostics and troubleshooting

Quality

14%

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 ./src/skills/bundled/doctor/SKILL.md

Quality

Content

14%

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

This skill reads as a dumped API reference rather than an actionable diagnostic guide. It is excessively verbose, listing every method and property without prioritization or workflow structure. It lacks a clear troubleshooting sequence with validation checkpoints, and all content is crammed into a single file with no progressive disclosure.

Suggestions

Add a clear diagnostic workflow at the top: 'Run /doctor quick → identify failing components → run /doctor <component> → apply fix from Common Issues → re-run to verify', with explicit validation steps.

Move the full TypeScript API reference to a separate REFERENCE.md and keep only a quick-start example (createDoctorService + runDiagnostics) in the main skill.

Remove redundant console.log examples for each check method — a single pattern showing how to interpret check results is sufficient; Claude can generalize to other methods.

Cut the Best Practices section entirely (generic advice Claude already knows) and trim the status/result tables to a single concise reference.

Dimension	Reasoning	Score
Conciseness	The content is extremely verbose at ~200+ lines, serving as a full API reference document. It exhaustively lists every method, every property, every check result with console.log examples that are largely redundant. Much of this (status levels, check result meanings, best practices like 'run regularly') is information Claude already knows or could infer.	1 / 3
Actionability	The code examples are concrete and appear executable with specific imports and method calls. However, they depend on a 'clodds/doctor' package whose existence and API are unverifiable, and many examples are just console.log wrappers around returned properties rather than demonstrating meaningful usage patterns or decision-making.	2 / 3
Workflow Clarity	There is no clear diagnostic workflow or troubleshooting sequence. The content lists individual checks and common issues but never sequences them into a coherent troubleshooting process (e.g., 'run quick check first, then drill into failing components, then apply fixes and re-verify'). No validation or feedback loops are present for a domain where they matter.	1 / 3
Progressive Disclosure	This is a monolithic wall of content with no references to external files. The full API reference, CLI commands, common issues, and best practices are all inlined. The API reference section alone could be a separate REFERENCE.md, and common issues could be a TROUBLESHOOTING.md.	1 / 3
	Total	5 / 12 Passed

Description

14%

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

This description is too vague and generic to be useful for skill selection. It lacks concrete actions, explicit trigger guidance, and sufficient specificity to distinguish it from other infrastructure or operations-related skills. It reads more like a category label than a functional skill description.

Suggestions

List specific concrete actions the skill performs, e.g., 'Checks system logs, monitors CPU/memory/disk usage, diagnoses network connectivity issues, analyzes error messages, and identifies failing services.'

Add an explicit 'Use when...' clause with natural trigger terms, e.g., 'Use when the user reports system slowness, service outages, high resource usage, error logs, or asks to diagnose server or infrastructure problems.'

Narrow the scope to a specific system type or domain (e.g., Linux servers, Docker containers, cloud infrastructure) to reduce conflict risk with other potentially overlapping skills.

Dimension	Reasoning	Score
Specificity	The description uses vague, abstract language ('health diagnostics and troubleshooting') without listing any concrete actions like checking logs, monitoring CPU usage, analyzing error codes, or restarting services.	1 / 3
Completeness	The description weakly addresses 'what' (diagnostics and troubleshooting) but provides no 'when' clause or explicit trigger guidance, and the 'what' itself is too vague to be useful.	1 / 3
Trigger Term Quality	Terms like 'diagnostics' and 'troubleshooting' are somewhat relevant keywords users might use, but 'system health' is generic and the description misses common variations like 'logs', 'errors', 'performance', 'monitoring', 'uptime', or specific system types.	2 / 3
Distinctiveness Conflict Risk	'System health diagnostics and troubleshooting' is extremely broad and could conflict with many skills related to DevOps, monitoring, logging, networking, server management, or any infrastructure-related skill.	1 / 3
	Total	5 / 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: alsk1992/CloddsBot
Commit: e71a5f6

Reviewed: 3 months ago

Table of Contents

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