CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

ralph-wiggum-v2

Autonomous TDD development loop with parallel agent swarm, category evolution, and convergence detection. Use when running autonomous game development, quality improvement loops, or comprehensive codebase reviews.

Quality

70%

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 ./skills/ralph-wiggum-v2/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

56%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-structured orchestration skill with concrete schemas, explicit convergence criteria, and a validation-rich loop, but it is held back by redundancy (Workflow vs Iteration Loop vs Hard Requirements), several execution steps with no commands attached, and zero progressive disclosure for a document of this size.

Suggestions

Deduplicate the process description: merge the "Workflow" phases, the "Iteration Loop" pseudocode, and the "Hard Requirements" checklist into one canonical loop so each rule appears exactly once.

Attach executable commands to the currently vague steps — test suite run, "TypeScript strict mode check", "Build production bundle", and "Verify game loads and plays" (e.g. the actual npm scripts to invoke).

Move the Review Styles catalog and the state/categories JSON schemas into reference files (e.g. references/review-styles.md, references/schemas.md) with one-line pointers from SKILL.md to cut the main file roughly in half.

DimensionReasoningScore

Conciseness

The body is mostly data-dense (style tables, schemas, loop pseudocode) with no concept over-explanation, but it is noticeably redundant: the "Workflow" phases restate the "Iteration Loop" block, "Hard Requirements" repeats Phase 5's convergence criteria, and "Overview" repeats the frontmatter description. It fits anchor 3 — mostly efficient but could be tightened into one canonical loop.

3 / 5

Actionability

Concrete elements exist (exact state/categories schemas, "10 consecutive clean iterations", "All category scores >= 95/100"), but several steps lack executable specifics: "Verify game loads and plays", "Bootstrap categories from codebase structure if empty", and "TypeScript strict mode check" name no command, and the LOOP block is pseudocode. This matches anchor 3 — some concrete guidance but incomplete.

3 / 5

Workflow Clarity

The iteration loop is clearly sequenced with explicit validation checkpoints and a feedback loop ("Verify test passes", "Run full test suite", "IF dirty: consecutiveCleanIterations = 0", plus a 5-step Final Verification), so the batch-operation cap does not apply. Not 5 because "Meta-review (every 5 iterations)" is undefined and the duplicated Phase/LOOP presentations create ambiguity.

4 / 5

Progressive Disclosure

The file is well-sectioned with headers and tables, but everything is inline in a ~277-line SKILL.md: the ~60-line review-style catalog and both JSON schemas clearly belong in separate reference files, and no bundle files exist at all. Anchor 3 fits — real structure, but content that should be separate is inline.

3 / 5

Total

13

/

20

Passed

Description

70%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 solid description with an explicit "Use when..." clause covering three natural trigger phrases and a mostly distinct niche. Its main weakness is the noun-phrase "what" that names features rather than concrete verb-led actions, leaving it slightly short of the top anchors.

Suggestions

Rewrite the capability sentence as verb-led concrete actions, e.g. "Spawns parallel review agents, writes failing tests before each fix, and iterates until category scores converge" instead of the noun-phrase feature list.

Add one or two natural synonyms to the trigger clause (e.g. "code review", "test-driven development loop") to broaden natural-term coverage.

DimensionReasoningScore

Specificity

"Autonomous TDD development loop with parallel agent swarm, category evolution, and convergence detection" names the domain and a few concrete capabilities, but as noun-phrase features rather than verb-led actions like "reviews code, writes failing tests, fixes issues". It matches anchor 3: domain plus 1-2 concrete capabilities, not a comprehensive list of specific actions.

3 / 5

Completeness

Both what ("Autonomous TDD development loop with parallel agent swarm...") and an explicit when ("Use when running autonomous game development...") are present. Not 5 because the "what" is a feature list rather than concrete actions and the "when" could be more specific; clearly above anchor 3 since the when clause is explicit.

4 / 5

Trigger Term Quality

"autonomous game development, quality improvement loops, or comprehensive codebase reviews" provides three distinct natural trigger phrases a user might say. It falls short of anchor 5 only because common synonyms like "code review", "test-driven", or "refactoring loop" are missing.

4 / 5

Distinctiveness Conflict Risk

"TDD development loop with parallel agent swarm" is a distinct niche, but the trigger phrase "comprehensive codebase reviews" overlaps generic code-review skills. Minor overlap risk with closely related skills fits anchor 4; not 5 due to that overlap, not 3 since the core triggers are distinctive.

4 / 5

Total

15

/

20

Passed

Validation

100%

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

fernandezbaptiste/Skrillz

Path

skills/ralph-wiggum-v2/SKILL.md

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.