CtrlK
BlogDocsLog inGet started
Tessl Logo

error-debugging-error-trace

You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging, and ensure teams can quickly identify and resolve production issues.

54

Quality

61%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/error-debugging-error-trace/SKILL.md

The canonical home for this skill is error-debugging-error-trace in rmyndharis/antigravity-skills

SKILL.md
Quality
Evals
Security

Quality

Content

61%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.

The skill body is a clean, well-structured overview with good progressive disclosure, but its instructions stay at a high-level abstract altitude without concrete commands or a spelled-out validation feedback loop for production operations.

Suggestions

Add concrete executable detail to the Instructions — e.g. sample alert-routing config, a named error-tracking service setup snippet, or a concrete 'send a test error and confirm it is grouped/alerted' validation command.

Spell out the validation feedback loop explicitly: 'Validate with test errors; if alerts/grouping fail, adjust config and re-validate before enabling in production.'

Remove the duplicated description line (the frontmatter already states it) and consolidate the single playbook reference to one place to tighten conciseness toward 5.

DimensionReasoningScore

Conciseness

The ~40-line body is lean with no concept tutorials or padding, but it duplicates the frontmatter description verbatim on line 11 and references the playbook twice (Instructions and Resources), which are trimmable, so it sits at the efficient-but-could-trim 4 anchor rather than 5.

4 / 5

Actionability

Instructions are an organized high-level list ('Assess current error capture', 'Define severity levels', 'Configure logging, tracing, and alert routing') with one mildly concrete step ('Validate signal quality with test errors'), but no specific commands, configs, named services, or concrete steps, landing just above the 2 floor at 3.

3 / 5

Workflow Clarity

The five steps form a clear sequence and include a validation step ('Validate signal quality with test errors'), but for a production-affecting batch operation the validation is abstract with no explicit fix-and-retry feedback loop, so it matches the 3 anchor for steps-with-validation-gaps.

3 / 5

Progressive Disclosure

The body is a well-organized overview with a clearly signaled one-level-deep reference to 'resources/implementation-playbook.md', but no bundle files (references/, scripts/, assets/) are present, so the referenced playbook file is absent — good disclosure structure with a minor missing-target gap, placing it at 4 rather than 5.

4 / 5

Total

14

/

20

Passed

Description

61%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.

The description conveys clear capabilities with good trigger-term coverage and a distinct niche, but it lacks an explicit 'Use when' clause and uses second-person voice, capping completeness at 3 and reducing specificity by one point.

Suggestions

Add an explicit 'Use when...' trigger clause, e.g. 'Use when setting up error monitoring, configuring production alerts, or improving incident triage.'

Switch to third-person voice ('Sets up error tracking systems...') to meet the voice requirement and recover the specificity point.

Include common synonyms/tool names (e.g. 'monitoring', 'crash reporting', 'Sentry', 'Datadog') to push trigger-term coverage toward comprehensive.

DimensionReasoningScore

Specificity

Lists four concrete actions ('Set up error tracking systems, configure alerts, implement structured logging, and ensure teams can quickly identify and resolve production issues'), but they remain high-level rather than granular, and the second-person voice ('You are an error tracking and observability expert') triggers the required 1-point specificity reduction from 4 to 3.

3 / 5

Completeness

The 'what' is clearly stated (set up tracking, alerts, logging, resolve production issues), but there is no explicit 'Use when...' trigger clause, so per the judging guideline a missing trigger clause caps completeness at 3.

3 / 5

Trigger Term Quality

Contains natural terms users would say — 'error tracking', 'observability', 'alerts', 'structured logging', 'production issues' — but misses common synonyms and tool names like 'monitoring', 'crash reporting', 'Sentry', so it falls short of the comprehensive 5 anchor.

4 / 5

Distinctiveness Conflict Risk

The 'error tracking and observability expert' framing with alerting/logging/production-issue actions carves a mostly distinct niche with only minor overlap risk against generic monitoring or logging skills, matching the 4 anchor.

4 / 5

Total

14

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.