CtrlK
BlogDocsLog inGet started
Tessl Logo

stream-chain

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

66

1.00x
Quality

50%

Does it follow best practices?

Impact

100%

1.00x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./.claude/skills/stream-chain/SKILL.md

The canonical home for this skill is stream-chain in ruvnet/agentic-flow

SKILL.md
Quality
Evals
Security

Quality

Content

46%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 body provides genuinely actionable CLI guidance with concrete syntax and options, but it is a padded monolith: redundant example sections, a restating conclusion, no validation checkpoints in its workflows, and zero use of progressive disclosure via separate files. It needs significant trimming and restructuring.

Suggestions

Cut redundant sections ('Examples Repository', 'Conclusion', 'Performance Characteristics', 'Related Skills') and move example catalogs into a separate examples/ or references/ file, keeping SKILL.md as a lean overview with clear links.

Add explicit validation/verification steps to the pipeline workflows (e.g., a per-step check that output is non-empty or valid before proceeding, and what to do on failure).

Consolidate the repeated run/pipeline command examples into a small set of distinct, representative examples instead of near-duplicate variations in multiple sections.

DimensionReasoningScore

Conciseness

The 563-line body is noticeably verbose: the 'Examples Repository' largely repeats examples already shown, the 'Conclusion' restates the overview, and 'Performance Characteristics'/'Related Skills' sections add padding with no operational value. This goes beyond 'some unnecessary explanation' into multiple padded sections.

2 / 5

Actionability

The content is mostly executable: concrete copy-paste CLI commands, explicit syntax forms, options tables with defaults, and worked examples ('claude-flow stream-chain run ... --timeout 45 --verbose'). Minor gaps remain, such as no sample command output to show what success looks like.

4 / 5

Workflow Clarity

Pipeline steps are clearly listed (e.g., 'Structure Analysis -> Issue Detection -> Recommendations'), but there are no validation checkpoints between steps, and verification appears only as a best-practice suggestion rather than a workflow requirement. Per the guidelines, batch multi-step operations without validation cap workflow clarity at 3.

3 / 5

Progressive Disclosure

There are no bundle files (references/, scripts/, assets/) and no external references at all — pipeline catalogs, the custom-config reference, troubleshooting, and extensive examples are all inlined in a single 560-line document. Content that clearly belongs in separate files is inlined, matching the anchor for minimal structure despite the presence of section headers.

2 / 5

Total

11

/

20

Passed

Description

53%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 communicates a clear niche with a well-formed 'what', but it has no 'when to use' trigger clause and relies on somewhat technical phrasing. Adding explicit 'Use when...' scenarios and more natural trigger terms would lift completeness and trigger quality.

Suggestions

Add an explicit 'Use when...' clause (e.g., 'Use when chaining agent outputs into sequential pipelines or transforming data across multiple stages').

Include natural trigger phrases users would say, such as 'multi-step workflow', 'agent pipeline', or 'pass output to the next step', rather than relying on 'Stream-JSON chaining' jargon.

Name one or two more concrete capabilities (e.g., 'run custom prompt sequences' or 'execute predefined analysis/refactor/test pipelines') to strengthen specificity.

DimensionReasoningScore

Specificity

The description names its domain ('Stream-JSON chaining') and capability areas ('multi-agent pipelines, data transformation, and sequential workflows') but lists no concrete actions comparable to 'extract text' or 'fill forms'. It fits the anchor for naming a domain with 1-2 concrete actions, not the several-specific-actions level above.

3 / 5

Completeness

The 'what' is clear (chaining for pipelines, data transformation, sequential workflows), but there is no 'Use when...' clause or equivalent trigger guidance, which caps completeness at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

Terms like 'multi-agent', 'pipelines', and 'data transformation' are plausible user phrasings, but 'Stream-JSON chaining' is technical jargon and common variations or synonyms users would actually say are missing. Some relevant keywords, but coverage is not comprehensive.

3 / 5

Distinctiveness Conflict Risk

'Stream-JSON chaining' identifies a fairly distinct niche, with only minor overlap risk against adjacent orchestration skills (e.g., swarm coordination, multi-agent workflows). It is mostly distinct but lacks explicit triggers that would make conflict risk minimal.

4 / 5

Total

13

/

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 (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

14

/

16

Passed

Repository
ruvnet/RuView
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.