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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

65%

Does it follow best practices?

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SecuritybySnyk

Passed

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Fix and improve this skill with Tessl

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

SKILL.md
Quality
Evals
Security

Quality

Content

48%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 has a genuinely strong process skeleton — clearly sequenced stages, explicit quality gates, and thorough failure-recovery and escalation protocols. However, it is severely padded with redundant restatements and fabricated example output, its code blocks are pseudocode against non-existent APIs, and it is a monolith with a dangling reference to a missing examples/ directory.

Suggestions

Cut the duplicated pipeline descriptions (Workflow Modes, Integration Points, and Quick Reference largely restate the Overview and stage sections) and remove the fabricated sample metrics/report; keep one canonical statement of each gate and recovery rule.

Replace the invented TypeScript APIs (recallMemory, storeMemory, task()) with real, executable instructions or commands for invoking the sibling skills and reading/writing the .multi-ai-context/ state files.

Move the final-report template, escalation format, and state-file schemas into reference files (and actually create the referenced examples/ directory), so SKILL.md is a lean overview with well-signaled one-level-deep references.

DimensionReasoningScore

Conciseness

The ~870-line body restates the same pipeline in the Overview, Complete Workflow, Workflow Modes, Quick Reference, and Integration Points sections, and pads it with fabricated illustrative blocks (a full sample final report, fake commit lists and metrics like "92/100, coverage 96%"). This matches the anchor for noticeably verbose with several padded sections, though it does not explain basic concepts Claude already knows, keeping it above anchor 1.

2 / 5

Actionability

There is some concrete guidance (state file paths like .multi-ai-context/plan.json, a cp command, gate checklists), but the TypeScript blocks are pseudocode against invented APIs (recallMemory, storeMemory, task()) and sibling-skill invocation is only hand-waved ("Use multi-ai-planning to create plan..."). This fits the anchor for some concrete but incomplete guidance relying on pseudocode.

3 / 5

Workflow Clarity

The five stages are clearly sequenced, each with an explicit quality gate, an if-fail recovery path, retry limits, and an escalation protocol — matching anchor 5's shape. It sits at anchor 4 because the actual execution mechanics (how to invoke each sibling skill, what commands to run) are implicit behind pseudocode and verbose templates.

4 / 5

Progressive Disclosure

Section structure with headers and summary tables exists, but the monolithic ~870 lines inline content that belongs in separate reference files (final report template, escalation format, state JSON schemas), and the only external pointer — "For examples, see examples/." — references a directory that does not exist in the bundle. This fits the anchor for some structure with inline content that should be separate and weakly signaled references.

3 / 5

Total

12

/

20

Passed

Description

67%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 clearly communicates what the skill does and when to use it, with a named pipeline and an explicit Use-when clause. Its main weaknesses are jargon-heavy, abstract trigger phrasing and a slight over-reliance on marketing language rather than natural user terms.

Suggestions

Rewrite the trigger clause with natural user phrases, e.g. "Use when the user asks to build a complete feature end-to-end, take a feature from idea to production, or run the full research-to-verification pipeline" instead of "executing production-grade development cycles end-to-end".

Trim redundant phrasing ("Complete development workflow orchestrator... Single-command complete workflows") and make the listed capabilities more concrete, e.g. naming what the quality gates check and what failure recovery does.

DimensionReasoningScore

Specificity

The description lists several concrete actions ("quality gates, failure recovery, and state management" plus the named 5-stage pipeline research → verification), matching the anchor for several specific actions with minor gaps. It falls short of anchor 5 because the actions remain fairly abstract rather than comprehensively concrete.

4 / 5

Completeness

Both a clear 'what' (orchestrating the 5-stage multi-ai pipeline with gates, recovery, and state management) and an explicit "Use when..." clause are present. The 'when' triggers are explicit but less concrete than the anchor-5 example, which cites user-mentionable artifacts, so anchor 4 is the best fit.

4 / 5

Trigger Term Quality

Trigger phrases like "implementing complete features", "full pipeline", and "end-to-end" are plausible user language, but the clause is jargon-heavy ("production-grade development cycles") and misses common natural variations such as "build a feature" or "from idea to production". This matches the anchor for some relevant keywords with missing synonyms rather than good coverage.

3 / 5

Distinctiveness Conflict Risk

It occupies a clear niche — orchestrating the named multi-ai skill suite — distinct from generic skills. Minor overlap risk remains with the closely related sibling skills it invokes (e.g., multi-ai-implementation would also trigger on "implement feature"), which keeps it below anchor 5.

4 / 5

Total

15

/

20

Passed

Validation

87%

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

CriteriaDescriptionResult

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

Reviewed

Table of Contents

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