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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

72%

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SecuritybySnyk

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Fix and improve this skill with Tessl

tessl review fix ./skills/end-to-end-orchestrator/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

51%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 — an unambiguous five-stage pipeline with quality gates, bounded retries, rollback, and escalation at every step — but it is significantly padded (triply-repeated gate definitions, fabricated sample outputs) and its code examples are largely pseudocode. Structure is the main weakness: it is a monolithic file with a dangling examples/ reference instead of a lean overview pointing to real bundle files.

Suggestions

Cut the padding: the illustrative final report (~55 lines), the fabricated escalation narrative, and the per-stage "What It Does/What It Provides" restatements can be removed or compressed — the Quick Reference already repeats the stage/time/gate table, so keep gates defined in exactly one place.

Replace the non-executable TypeScript pseudocode (recallMemory, readFile, task({...})) with either real runnable commands or brief natural-language instructions to the coordinated skills, keeping only the genuinely executable bash snippets.

Fix progressive disclosure: create the referenced examples/ directory and move the sample report, escalation example, and stage-by-stage details into it (or into references/), leaving SKILL.md as a lean overview with well-signaled one-level-deep links.

DimensionReasoningScore

Conciseness

The ~870-line body is noticeably padded: quality-gate thresholds are restated three times (pipeline diagram, per-stage sections, Quick Reference tables), and it inlines a fabricated ~55-line sample final report ("Coverage: 96%", "Total Time: 11.3 hours", commits "abc123"/"def456") plus a fabricated escalation narrative and per-stage "What It Does/What It Provides" sections that restate the preceding process — the redundancy is pervasive, not occasional, so anchor 2 rather than 3.

2 / 5

Actionability

Real, executable bash commands appear ("cp plans/[plan-id]/plan.json .multi-ai-context/plan.json", "cat .multi-ai-context/pipeline-state.json | jq ..."), but most code blocks are non-executable pseudocode — "await recallMemory({...})", bare "readFile('.multi-ai-context/plan.json')", "task({description, prompt})" — which the guidelines explicitly penalize; this is exactly anchor 3 (pseudocode instead of executable code, missing key details) rather than 4.

3 / 5

Workflow Clarity

The five-stage pipeline is explicitly sequenced with per-stage ✅-checklist quality gates, retry limits ("max 2 retries per layer", "doom loop prevention (max 3 retries)"), rollback to checkpoints, re-verify-from-failed-layer ("not all 5"), and a seven-condition escalation protocol with a structured format — clear sequence, explicit validation, and feedback loops matching the anchor-5 example.

5 / 5

Progressive Disclosure

A ~22KB monolithic SKILL.md inlines content that clearly belongs in separate files (the illustrative final report and escalation example), and its only reference — "For examples, see examples/." — points to a nonexistent directory (no references/, scripts/, assets/, or examples/ exist in the bundle), which is worse than the buried-but-present references of anchor 3 and fits anchor 2.

2 / 5

Total

12

/

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.

A strong description: it explicitly states both what the skill does and when to use it, with concrete trigger conditions and a fully enumerated pipeline. Its weaknesses are modest — abstract capability nouns in place of concrete actions, some missing natural synonyms, and inherent overlap with the five sibling skills it coordinates.

DimensionReasoningScore

Specificity

Enumerates a complete, specific pipeline ("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"), but phrases like "quality gates" and "state management" are capability nouns rather than the concrete verb+object actions of the anchor-5 example, leaving minor gaps.

4 / 5

Completeness

Clearly answers both "what" (orchestrates the five-stage research→verification pipeline with quality gates, failure recovery, and state management, delivering production-ready code) and "when" via an explicit "Use when implementing complete features requiring full pipeline, coordinating multiple skills automatically, or executing production-grade development cycles end-to-end" clause with concrete triggers, matching the anchor-5 example.

5 / 5

Trigger Term Quality

Natural trigger phrases are present ("implementing complete features", "full pipeline", "production-grade development cycles", "end-to-end"), giving good coverage, but common variants like "ship/build a feature" are missing and "multi-ai skills" is internal jargon — solidly anchor 4 rather than the synonym-level comprehensiveness of 5 or the sparser coverage of 3.

4 / 5

Distinctiveness Conflict Risk

The orchestrator role over the five named sibling skills is a clear niche, but triggers like "implementing complete features" could plausibly fire the coordinated skills themselves (multi-ai-implementation, multi-ai-planning) — minor overlap risk with closely related skills, i.e., anchor 4 rather than the minimal-conflict clarity of 5.

4 / 5

Total

17

/

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

skills/end-to-end-orchestrator/SKILL.md

Reviewed

Table of Contents

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