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soccer-agent-toolbelt

Soccer analytics agent toolbelt. Gives Claude Code direct access to the Oracle-backed match data, ML predictions, and three-tier memory. Use when answering questions about football matches, building on the soccer agent, or exploring the World Cup dataset.

64

Quality

76%

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 ./workshops/soccer-analytics-agent/.claude/skills/soccer-agent-toolbelt/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

77%

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

A highly actionable, well-structured reference with excellent executable examples and clear validation loops. Its main weaknesses are duplicated rule statements across sections and a monolithic layout that forgoes progressive disclosure into separate reference files.

Suggestions

De-duplicate the hybrid-first and observability rules: state each once and cross-reference from the Pitfalls section rather than restating.

Move the 13-tool API reference and/or the Oracle pitfalls into separate reference files under references/, keeping SKILL.md as a concise overview with one-level-deep links.

DimensionReasoningScore

Conciseness

The body is dense and mostly high-signal Oracle-specific knowledge, but the hybrid-first rule and the observability rule are each stated twice (once in the rules sections and again in the Pitfalls section), so some tokens could be trimmed.

2 / 3

Actionability

It provides fully executable, copy-paste-ready guidance throughout, including the run_tool.py dispatcher invocations with concrete JSON args, curl pipelines, and a complete CLOB-materialization code block.

3 / 3

Workflow Clarity

Multi-step processes are clearly sequenced with validation checkpoints, notably the observability feedback loop ('if this returns no rows... run init_memory.py and verify.py; the verifier must report...') and the three-step 'Adding your own tool' sequence.

3 / 3

Progressive Disclosure

The file is well-organized into clear sections but is a monolithic ~167-line document with no bundle files, and substantial content such as the 13-tool API reference and the lengthy pitfalls section could be split into separate reference files.

2 / 3

Total

10

/

12

Passed

Description

75%

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 solid description that clearly states both its purpose and an explicit trigger, with a distinctive niche. It is held back from the top tier by capability framing that lists accessed objects rather than discrete actions and by somewhat narrow trigger-term coverage.

Suggestions

Replace 'Gives Claude Code direct access to...' with a list of concrete actions (e.g. 'Query match data, run ML match predictions, and read/write three-tier memory').

Broaden trigger terms to include common variations users would say, such as 'soccer matches', 'match predictions', or 'team statistics'.

DimensionReasoningScore

Specificity

Names the domain and several capabilities ('direct access to the Oracle-backed match data, ML predictions, and three-tier memory') but frames them as access to objects rather than listing multiple discrete concrete actions, so it is not comprehensive.

2 / 3

Completeness

It explicitly answers both what it does ('Gives Claude Code direct access to...match data, ML predictions, and three-tier memory') and when to use it via an explicit 'Use when...' trigger clause.

3 / 3

Trigger Term Quality

The 'Use when answering questions about football matches, building on the soccer agent, or exploring the World Cup dataset' clause provides some natural terms but limited variations, missing common phrasings like 'soccer matches' or 'match predictions'.

2 / 3

Distinctiveness Conflict Risk

The Oracle-backed soccer/World-Cup analytics niche with terms like 'soccer agent' and 'World Cup dataset' is clearly distinct and unlikely to trigger for unrelated skills.

3 / 3

Total

10

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 4 missing

Warning

Total

15

/

16

Passed

Repository
oracle-devrel/oracle-ai-developer-hub
Reviewed

Table of Contents

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