Name: arn-code-standard
Rating: 63.2 (1 reviews)
Author: AppsVortex

arn-code-standard

This skill should be used when the user says "standard", "standard mode", "standard implementation", "arn-code-standard", "standard change", "medium change", "standard feature", "standard fix", or wants a mid-ceremony implementation for a change that needs lightweight architectural context (spec-lite) and task-tracked execution but not the full feature-spec/plan pipeline. Bridges the gap between arn-code-swift and the full thorough pipeline. Includes spec-lite generation, structured plan, in-session execution, review-lite, and a unified change record.

Quality

76%

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/arn-code/skills/arn-code-standard/SKILL.md

Quality

Content

62%

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

This skill is highly actionable and has excellent workflow clarity with comprehensive error handling and validation checkpoints. However, it is severely over-verbose — the sketch-aware promotion logic, repeated preference check patterns, and exhaustive conditional branching inflate the token cost dramatically. Much of this detail (sketch manifest handling, preference lookup chains, false-negative follow-up logic) should be extracted into reference files rather than inlined in the main skill body.

Suggestions

Extract the sketch promotion logic (Step 2c and Step 4's sketch-aware sections) into a dedicated reference file like `references/sketch-promotion.md` — this alone would save ~100 lines from the main body.

Abstract the repeated preference check pattern (used identically for sketch-preview and simplification) into a single reference file like `references/preference-gate.md` with parameterized instructions, then reference it twice with different parameters.

Compress the specialist pre-check and false-negative follow-up sections (Step 2a-2c) — the term lists and boolean logic could be in a reference file, with the main body just saying 'Apply specialist pre-check per references/specialist-pre-check.md'.

Remove the Pipeline Position ASCII diagram and the detailed Artifacts table at the end — these are informational rather than instructional and add tokens without changing Claude's behavior.

Dimension	Reasoning	Score
Conciseness	This skill is extremely verbose at ~400+ lines, with extensive procedural detail that could be dramatically compressed. It explains preference lookup chains, sketch manifest status handling, and conditional branching in exhaustive detail that Claude could infer from much shorter instructions. Many sections repeat patterns (preference check → gate → follow-up) that could be abstracted into a shared reference.	1 / 3
Actionability	The skill provides highly specific, concrete guidance at every step: exact file paths, specific JSON field names and values, precise conditional logic, exact user-facing messages, and clear agent dispatch instructions. Every step has unambiguous deliverables and the artifact schemas are fully specified.	3 / 3
Workflow Clarity	The workflow is clearly sequenced with numbered steps, explicit validation checkpoints (spec-lite approval, plan approval, test verification, review-lite with verdict logic), and well-defined feedback loops (self-heal up to 3 attempts, re-review after fixes, adjust cycles). Error handling is comprehensive with specific recovery paths for each failure mode.	3 / 3
Progressive Disclosure	The skill references external files appropriately (step-0-fast-path.md, specialist-pre-check.md, standard-plan-template.md, swift-review-checklist.md, pattern-refresh.md, preferences-schema.md), but the main body contains enormous amounts of inline detail that should be in reference files — particularly the sketch promotion logic (~100 lines), preference check patterns (repeated 2x), and the detailed componentMapping handling. No bundle files were provided to verify references exist.	2 / 3
	Total	9 / 12 Passed

Description

89%

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 trigger term coverage and completeness, clearly defining when to use the skill with explicit trigger phrases and distinguishing it from related skills. Its main weakness is that the concrete capabilities are somewhat jargon-heavy and compressed into a brief list at the end, making it harder to understand what the skill actually does without prior context of the workflow.

Suggestions

Expand the capability descriptions to use more universally understandable language — e.g., instead of 'spec-lite generation,' say 'generates a lightweight specification document summarizing the change's architecture and scope.'

Dimension	Reasoning	Score
Specificity	The description names several concrete actions like 'spec-lite generation, structured plan, in-session execution, review-lite, and a unified change record,' but these are listed briefly at the end and use internal jargon rather than universally understood terms. The bulk of the description focuses on trigger terms rather than explaining what the skill concretely does.	2 / 3
Completeness	The description explicitly answers both 'what' (spec-lite generation, structured plan, in-session execution, review-lite, unified change record) and 'when' (extensive list of trigger phrases and contextual guidance about when to use it vs. swift or full pipeline). The 'when' is very explicit.	3 / 3
Trigger Term Quality	The description provides extensive trigger terms including 'standard', 'standard mode', 'standard implementation', 'arn-code-standard', 'standard change', 'medium change', 'standard feature', 'standard fix', and contextual triggers like 'mid-ceremony implementation'. These are natural phrases a user in this workflow would say.	3 / 3
Distinctiveness Conflict Risk	The description clearly positions this skill in a specific niche between 'arn-code-swift' and the 'full thorough pipeline,' with very specific trigger terms like 'arn-code-standard' and 'standard mode' that are unlikely to conflict with other skills. It explicitly differentiates itself from adjacent skills.	3 / 3
	Total	11 / 12 Passed

Validation

81%

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 — 9 / 11 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (552 lines); consider splitting into references/ and linking	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	9 / 11 Passed

Repository: AppsVortex/arness
Commit: b9084b6

Reviewed: about 1 month ago

Table of Contents

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