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sciomc

Orchestrate parallel scientist agents for comprehensive analysis with AUTO mode

29

Quality

23%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Risky

Do not use without reviewing

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/sciomc/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

39%

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

The skill defines a comprehensive research orchestration workflow with clear sequencing and validation steps, but suffers severely from verbosity and lack of progressive disclosure. At 350+ lines with no supporting bundle files, it dumps extensive schemas, templates, regex patterns, and configuration details inline that should be split into reference documents. The actionability is moderate—examples are illustrative but rely on pseudo-syntax rather than truly executable code.

Suggestions

Extract the report template, state.json schema, regex extraction patterns, and configuration reference into separate bundle files (e.g., REPORT_TEMPLATE.md, STATE_SCHEMA.md, TAG_PATTERNS.md) and reference them from the main skill.

Cut the routing decision guide table and parallel execution patterns section by at least 50%—the smart model routing table already conveys the key information, and multiple parallel pattern examples are redundant.

Remove or drastically condense the figure embedding protocol and figure types table—Claude understands markdown image embedding and doesn't need this explained.

Make Task invocations more concrete by clarifying the actual API/tool syntax rather than using illustrative pseudocode with parenthetical notation.

DimensionReasoningScore

Conciseness

The skill is extremely verbose at ~350+ lines. It over-explains concepts Claude already understands (parallel execution patterns, regex patterns, JSON schemas, report templates). Much of this content—like the full state.json schema, regex extraction patterns, report template, and figure embedding protocol—could be dramatically condensed or moved to reference files. The routing decision guide and multiple parallel execution pattern examples are redundant.

1 / 3

Actionability

The skill provides concrete examples of Task invocations, structured tags, and command usage, which is good. However, much of the code is pseudocode or template-style (e.g., `Task(subagent_type=...)` isn't real executable syntax, the regex patterns are illustrative but not tied to actual implementation, and the report template uses placeholder variables). The guidance is specific enough to follow but not truly copy-paste executable.

2 / 3

Workflow Clarity

The multi-stage workflow is clearly sequenced: Decomposition → Execution → Verification → Synthesis. The verification loop includes explicit cross-validation with conflict detection, and AUTO mode has clear iteration limits, state tracking, and promise-based completion signals. The batching strategy for >20 concurrent agents adds a practical constraint checkpoint.

3 / 3

Progressive Disclosure

This is a monolithic wall of text with no bundle files to reference. The state.json schema, regex patterns, report template, figure embedding protocol, and configuration details should all be in separate reference files. Everything is inlined into a single massive document with no external references, making it a poor use of progressive disclosure.

1 / 3

Total

7

/

12

Passed

Description

7%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This description is too vague and jargon-heavy to be effective for skill selection. It fails to explain what specific actions are performed, what domain it applies to, or when Claude should choose it. The use of internal terminology like 'AUTO mode' and 'scientist agents' without context makes it nearly unusable for matching user requests.

Suggestions

Add a 'Use when...' clause specifying the scenarios or user requests that should trigger this skill, e.g., 'Use when the user requests multi-faceted data analysis requiring parallel processing or mentions running multiple analyses simultaneously.'

Replace vague terms like 'comprehensive analysis' with specific concrete actions, e.g., 'Runs statistical tests, generates visualizations, and produces summary reports across multiple datasets in parallel.'

Include natural trigger terms that users would actually say, such as 'analyze data', 'run experiments', 'parallel analysis', or whatever domain-specific terms apply.

DimensionReasoningScore

Specificity

The description uses vague language like 'comprehensive analysis' and 'orchestrate parallel scientist agents' without specifying what concrete actions are performed. It doesn't explain what kind of analysis, what the agents do, or what outputs are produced.

1 / 3

Completeness

The description weakly addresses 'what' (orchestrate agents for analysis) and completely lacks a 'when' clause or any explicit trigger guidance for when Claude should select this skill.

1 / 3

Trigger Term Quality

The terms 'orchestrate', 'parallel scientist agents', and 'AUTO mode' are technical jargon that users would not naturally say. There are no natural keywords a user would use when needing this skill.

1 / 3

Distinctiveness Conflict Risk

The mention of 'parallel scientist agents' and 'AUTO mode' provides some distinctiveness since these are fairly specific concepts, but 'comprehensive analysis' is generic enough to potentially overlap with other analytical skills.

2 / 3

Total

5

/

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 (512 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
Yeachan-Heo/oh-my-claudecode
Reviewed

Table of Contents

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