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Documentation Index

Fetch the complete documentation index at: https://docs.getclaro.ai/llms.txt

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Analyse is where you understand the state of a catalogue and trigger the transformations that improve it. The module exposes two surfaces: Analyse (data-quality reporting) and Generative Engine (model-driven content operations).

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Analyse

Runs a data-quality assessment on a catalogue or a filtered record set. Output includes:
  • Headline metrics — total records, unique entries, duplicate estimates, columns analysed.
  • Strengths and attention areas — narrative summary of what’s good and what’s weak.
  • Prioritized recommendation — the single highest-leverage next operation to run.
  • Per-field scores — fill rate, uniqueness, length variance, with an excellent / good / fair / poor rating.
  • Distribution stats — mean, median, standard deviation, min, max — for numeric columns.
  • Critical issues — issues with one-click follow-on actions:
    • Trigger Enrichment on a low-fill column
    • Review and Validate on suspicious distributions
    • Find Duplicates on suspected entity collisions
    • Generate Taxonomy when category coverage is poor
  • Overall Data Quality Score — out of 100, computed from per-field scores weighted by the importance configured in the catalogue’s Config tab.
Analyse is non-destructive — it reads records and writes a report, never modifies data.

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When to run

  • Before kicking off a new pipeline, to set a baseline.
  • After a large batch of new records, to spot regressions.
  • On a schedule (e.g. weekly), to track quality over time.
Reports are versioned; you can diff two reports to see what improved or regressed.

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Generative Engine

Model-driven generation operations that produce content from your records.
CapabilityOutput
DescriptionsLong-form product descriptions, optimized for SEO and brand voice.
Marketing copyShort copy variants — headlines, taglines, social posts.
Structured attribute extractionPull typed fields out of free-text descriptions or supplier blurbs.
Image alt-textAccessibility-compliant alt text from product images.
TranslationsMulti-language variants of any text attribute, with brand-voice consistency across locales.

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Configuration

For every Generative Engine job you choose:
  • Target attribute(s) — where the output is written.
  • Prompt — the instruction, with @attribute references to other fields on the same record.
  • Knowledge Bases — domain documents (brand guidelines, datasheets) the model can cite.
  • Model — Claro default (with confidence scoring and citations) or another available model.
  • Confidence thresholds — auto-apply, review, reject.
  • Length and format constraints — character limits, schema, allowed tones.
Outputs ship with confidence scores and citations to the sources used, so each generated value is auditable. Below-threshold outputs queue for review in Notifications.

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Tips

  • Reference other attributes by name with @ to ground generation in the record. “Write a 100-word description for @product_name based on @spec_summary, in the voice of @brand.”
  • Include a Knowledge Base of brand and category guidelines for consistency across thousands of generations.
  • Generate in batches and review confidence distributions before raising the auto-apply threshold.