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stream-chain

Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

53

1.00x
Quality

30%

Does it follow best practices?

Impact

100%

1.00x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./.claude/skills/stream-chain/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

27%

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

This skill is excessively verbose with heavy redundancy—the same pattern (bash command with string prompts) is repeated dozens of times across multiple sections (Quick Start, Examples, Advanced Use Cases, Examples Repository). The content lacks validation/verification steps in workflows and dumps everything into a single monolithic file. While the CLI syntax is concrete and copy-paste ready, the sheer volume of near-identical examples dilutes the useful information.

Suggestions

Cut content by at least 60%: consolidate Quick Start, Examples, Advanced Use Cases, and Examples Repository into 2-3 representative examples maximum, removing redundant bash command variations.

Add validation checkpoints to workflows: show how to verify each step's output before proceeding (e.g., checking step output, handling failures mid-chain, retry logic).

Split into multiple files: keep SKILL.md as a concise overview with Quick Start and syntax, then move pipeline details to PIPELINES.md, custom configuration to CONFIG.md, and examples to EXAMPLES.md.

Show actual output examples: include what a chain execution looks like (progress output, results format, error messages) so Claude knows what to expect and can verify correct behavior.

DimensionReasoningScore

Conciseness

Extremely verbose at ~350+ lines. Massive redundancy: the 'Examples' section repeats patterns already shown, the 'Advanced Use Cases' section adds more of the same bash examples, and the 'Examples Repository' at the end duplicates yet again. The conclusion restates what was already clear. Sections like 'Performance Characteristics' and 'Neural Pattern Training' add dubious value. Claude doesn't need explanations of what pipelines are or how context flows conceptually.

1 / 3

Actionability

Provides concrete CLI commands that are copy-paste ready, which is good. However, all examples are bash invocations with string prompts—there's no executable code showing how to programmatically define or extend chains, no actual output examples showing what results look like, and the custom pipeline JSON config is shown but never validated. The guidance is concrete but shallow—it's mostly variations of the same pattern.

2 / 3

Workflow Clarity

Pipeline steps are listed clearly (e.g., 1. Structure Analysis, 2. Issue Detection, 3. Recommendations), and the 'How Context Flows' section explains chaining. However, there are no validation checkpoints or error recovery feedback loops. The troubleshooting section is minimal and reactive rather than integrated into workflows. For multi-step operations that could fail at any stage, there's no guidance on verifying intermediate outputs.

2 / 3

Progressive Disclosure

Everything is in one monolithic file with no bundle files or external references. The 'Related Skills' section mentions other skills but provides no links. Content that could be split (predefined pipeline details, advanced use cases, examples repository, custom pipeline definitions) is all inline, creating a wall of text. The document would benefit enormously from splitting into overview + reference files.

1 / 3

Total

6

/

12

Passed

Description

32%

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 provides a high-level sense of the domain (JSON streaming in multi-agent contexts) but relies on technical jargon and abstract concepts without listing concrete actions. It critically lacks a 'Use when...' clause, making it difficult for Claude to know when to select this skill over others. The terms used are a mix of somewhat distinctive ('Stream-JSON chaining') and overly generic ('data transformation', 'sequential workflows').

Suggestions

Add an explicit 'Use when...' clause with trigger scenarios, e.g., 'Use when the user needs to chain JSON-based operations across multiple agents, build streaming data pipelines, or orchestrate sequential processing steps.'

List specific concrete actions instead of abstract concepts, e.g., 'Parses streaming JSON data, chains agent outputs as inputs to downstream agents, transforms data schemas between pipeline stages, and manages sequential workflow execution.'

Include natural user-facing keywords and file/format references like 'JSON streaming', 'NDJSON', 'pipeline orchestration', 'agent chaining', or 'workflow automation' to improve trigger term coverage.

DimensionReasoningScore

Specificity

Names the domain (Stream-JSON, multi-agent pipelines) and some actions (chaining, data transformation, sequential workflows), but these are fairly abstract and don't list concrete specific actions like 'parse JSON streams', 'route messages between agents', or 'transform data between pipeline stages'.

2 / 3

Completeness

Describes what it does at a high level but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per the rubric, a missing 'Use when...' clause caps completeness at 2, and the 'what' is also weak, so this scores a 1.

1 / 3

Trigger Term Quality

Includes some relevant terms like 'multi-agent pipelines', 'data transformation', and 'sequential workflows', but 'Stream-JSON chaining' is technical jargon that users are unlikely to naturally say. Missing common variations like 'JSON streaming', 'pipeline orchestration', 'agent coordination', or 'workflow automation'.

2 / 3

Distinctiveness Conflict Risk

'Stream-JSON' provides some specificity, but 'data transformation' and 'sequential workflows' are very broad terms that could overlap with many other skills involving data processing or workflow management. The description is somewhat specific but not clearly carved into a distinct niche.

2 / 3

Total

7

/

12

Passed

Validation

81%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation9 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (564 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
ruvnet/ruvector
Reviewed

Table of Contents

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