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rill-model

Detailed instructions and examples for developing model resources in Rill

69

1.36x
Quality

56%

Does it follow best practices?

Impact

93%

1.36x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/rill-model/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%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 is highly actionable thanks to extensive executable examples and good section structure, but it is weakened by a monolithic layout that inlines a large JSON schema and by the absence of an explicit build/validate workflow for its destructive and expensive operations.

Suggestions

Move the inlined JSON schema (the 'Reference documentation' block) into a separate references file and keep only a short property summary inline, cutting hundreds of tokens from the always-loaded body.

Add an explicit creation workflow with validation checkpoints, e.g. 1) scaffold model, 2) run with a dev partition, 3) verify row count/schema, 4) only then remove the dev limit / materialize, 5) add data-quality tests.

Split the long Examples catalog and dialect-specific notes into one-level-deep reference files (e.g. examples.md, connectors.md) with clearly signaled links from the overview.

DimensionReasoningScore

Conciseness

The prose is mostly efficient and assumes Claude's competence (e.g. tight Materialization/Incremental sections), but the ~640-line inlined JSON schema dump in 'Reference documentation' is a major token sink that largely restates machine-readable reference data; this matches anchor 3 ('Mostly efficient but includes some unnecessary ... could be tightened') rather than 4 because the schema block should be trimmed or outlined.

3 / 5

Actionability

The body provides ~25 copy-paste-ready YAML/SQL examples spanning the common cases (mock data, S3->DuckDB, BigQuery/Snowflake/MySQL sources, partition- and state-based incremental, ClickHouse schemas, dev partitions) plus concrete templating variables and dialect-specific snippets, matching anchor 5 ('Fully executable; copy-paste ready ... specific examples cover the common cases').

5 / 5

Workflow Clarity

Sections are logically ordered (materialize -> incremental -> partitions -> examples -> reference) and include cautionary best practices, but there is no explicit multi-step build/validate sequence with checkpoints for the risky operations it describes (expensive models, destructive incremental overwrites), matching anchor 3 ('sequence present but checkpoints missing or implicit').

3 / 5

Progressive Disclosure

The file has clear section headers and no nested/2+-level references, but everything is monolithically inlined into one ~1415-line file with no bundle files, including a large JSON schema block that clearly belongs in a separate reference; this matches anchor 3 ('Some structure ... content that should be separate is inline') rather than 2 because the headers give real navigability.

3 / 5

Total

14

/

20

Passed

Description

48%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 correctly identifies the Rill-model niche but relies on generic verbs and omits any 'Use when...' trigger guidance, leaving it vague on concrete capabilities and on when to invoke it. It is distinct yet under-specified.

Suggestions

Replace the generic 'developing' with concrete actions, e.g. 'Define and materialize SQL/YAML models, configure incremental and partitioned ingestion, and set refresh schedules in Rill'.

Add an explicit trigger clause such as 'Use when the user asks to create or edit Rill model resources, configure incremental/partitioned ingestion, or set up ETL transformations in a Rill project'.

Include natural synonyms users say — 'SQL model', 'Model YAML', 'ETL/transformation model', '.sql/.yaml' — to broaden trigger coverage.

DimensionReasoningScore

Specificity

The phrase 'developing model resources in Rill' names the domain but the only action verbs are the generic 'developing' and 'instructions and examples', with no concrete actions like materialize, partition, or run incremental loads; this matches anchor 2 ('Names the domain but actions are minimal or generic') and falls short of anchor 3 which requires 1-2 concrete actions.

2 / 5

Completeness

It states a clear 'what' ('developing model resources in Rill') but provides no 'Use when...' clause or equivalent trigger guidance, so per the judging guideline a missing 'when' caps completeness at 3 ('Has a clear what but when is missing or only weakly implied').

3 / 5

Trigger Term Quality

It surfaces the natural keywords 'Rill' and 'model' that a user would say, but omits common synonyms and variations a user might actually use ('SQL model', 'ETL', 'transformation', 'incremental model', '.yaml/.sql'), matching anchor 3 ('Some relevant keywords but missing common variations or synonyms').

3 / 5

Distinctiveness Conflict Risk

'Developing model resources in Rill' carves out a clear niche tied to a specific tool, giving it low overlap risk with unrelated skills, though the generic 'developing' verb leaves minor overlap with adjacent Rill resources; this sits above anchor 3 and approaches but does not fully reach anchor 5's distinct trigger phrases.

4 / 5

Total

12

/

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.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (1420 lines); consider splitting into references/ and linking

Warning

relative_links

Relative link issues: 7 missing, 3 suspicious

Warning

Total

14

/

16

Passed

Repository
rilldata/agent-skills
Reviewed

Table of Contents

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