Name: end-to-end-orchestrator
Rating: 59.2 (1 reviews)
Author: fernandezbaptiste

end-to-end-orchestrator

Complete development workflow orchestrator coordinating all multi-ai skills (research → planning → implementation → testing → verification) with quality gates, failure recovery, and state management. Single-command complete workflows from objective to production-ready code. Use when implementing complete features requiring full pipeline, coordinating multiple skills automatically, or executing production-grade development cycles end-to-end.

Quality

69%

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tessl review fix ./.claude/skills/end-to-end-orchestrator/SKILL.md

The canonical home for this skill is end-to-end-orchestrator in fernandezbaptiste/Skrillz

Quality

Content

55%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 body excels at workflow clarity with a well-sequenced, validated 5-stage pipeline and robust failure recovery, but it is significantly over-long and leans on pseudocode and large inlined templates instead of executable guidance and one-level-deep reference files.

Suggestions

Move the final-report template, progress-tracking JSON, parallel-execution TypeScript, and escalation format into separate reference files (e.g. references/report-template.md, references/state-schema.json) and link to them from the body to cut token load and fix the missing examples/ reference.

Replace the pseudocode TypeScript blocks (recallMemory, storeMemory, task()) with concrete, copy-paste-ready invocations or shell commands, or explicitly justify the pseudocode as illustrative.

Trim verbose 'What It Does'/'What It Provides' recap lists that restate information already implied by the stage purpose and quality gates.

Dimension	Reasoning	Score
Conciseness	The ~870-line body is noticeably verbose: large inlined templates (final report, progress-tracking JSON, escalation format, parallel-execution TypeScript) pad the token budget with illustrative rather than essential content, fitting the 'noticeably verbose; several padded sections' anchor rather than the mostly-efficient level 3.	2 / 5
Actionability	It offers some concrete guidance (bash cp/echo state-saving commands, explicit quality-gate checklists) but the core invocations are natural-language directives ('Use multi-ai-research for...') and the TypeScript blocks (recallMemory, storeMemory, task()) are pseudocode rather than executable code, matching the 'some concrete guidance but incomplete; pseudocode' anchor.	3 / 5
Workflow Clarity	The 5-stage pipeline is clearly sequenced with explicit validation checkpoints (quality gates at each stage), feedback loops for error recovery ('If Fail' → retry up to N → escalate), and doom-loop prevention, directly matching the level-5 anchor with explicit validation steps and checklists.	5 / 5
Progressive Disclosure	Section headers give it some structure, but bulk content (report templates, progress JSON, parallel-execution code, integration points) is inlined rather than split into reference files, and the lone 'see examples/.' reference points to a directory that does not exist, matching the 'some structure but content that should be separate is inline; references not clearly signaled' anchor.	3 / 5
	Total	13 / 20 Passed

Description

83%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 is strong: it clearly states both what the skill does and when to use it, with concrete actions and natural trigger phrases in third person. Its only weakness is slight overlap risk with broader orchestration skills and a few missing synonyms.

Dimension	Reasoning	Score
Specificity	Names the domain and lists several concrete actions — 'coordinating all multi-ai skills', 'quality gates, failure recovery, and state management', 'Single-command complete workflows from objective to production-ready code' — with only minor coverage gaps, fitting the 'lists several specific actions' anchor rather than the fully comprehensive level 5.	4 / 5
Completeness	Explicitly answers both 'what' (orchestrator coordinating multi-ai skills with quality gates, failure recovery, state management) and 'when' ('Use when implementing complete features requiring full pipeline, coordinating multiple skills automatically, or executing production-grade development cycles end-to-end'), matching the level-5 anchor with concrete trigger phrases.	5 / 5
Trigger Term Quality	Good keyword coverage with natural phrases users would say — 'implementing complete features', 'full pipeline', 'coordinating multiple skills automatically', 'production-grade development cycles end-to-end' — but a few common synonyms are missing, so it sits above the 'some relevant keywords' anchor (3) and below comprehensive (5).	4 / 5
Distinctiveness Conflict Risk	It carves a clear niche (end-to-end multi-ai pipeline orchestration) with distinct triggers, but 'coordinating multiple skills' and 'end-to-end workflow' terminology carries minor overlap risk with other generic workflow/orchestrator skills, placing it just below the minimal-conflict level 5.	4 / 5
	Total	17 / 20 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (879 lines); consider splitting into references/ and linking	Warning
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning

	Total	14 / 16 Passed

Repository: fernandezbaptiste/Skrillz
Path: .claude/skills/end-to-end-orchestrator/SKILL.md
Commit: 93ed392

Reviewed: 2 days ago

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