Site Analysis Handbook > Approaches > Nielsen Heuristics My List ♥ ()

Approach: Nielsen Heuristics

Run in Chimera Guardrails
Connected Claude or other chatbot to Chimera? Type: Run Chimera's get-skill tool with arguments {"skill_name": "inventory_from_template", "approach_slug": "nielsen-heuristics"}. Both arguments are required — pass approach_slug as shown. Then follow the workflow embedded in the response.

Jakob Nielsen's 10 Usability Heuristics are widely cited rules of thumb for interface usability — distilled by Nielsen in 1994 from a survey of usability problems and updated since. They are deliberately broad principles rather than specific guidelines, intended to be applied with judgment to whatever interface is in front of you.

Applied to web content as a rubric, the heuristics let you score every page on the same ten dimensions: how clearly the page communicates where the user is, whether its language matches how the audience actually thinks, whether users can recover from mistakes, whether the layout is consistent with the rest of the site, and so on.

Each page gets a score for each heuristic plus an overall score, so you can sort an inventory by usability, find your weakest pages or weakest dimensions, and use that to prioritize rework.

See Nielsen Heuristics fields below. Or show fields for all field types.
Nielsen H1 Visibility
Does the page keep users informed about where they are and what is going on? Look for breadcrumbs, clear page titles, current-section highlighting in navigation, and timely feedback for user actions.
General Usefulness:
Traditional Ease of Automation:
Compare with other User fields.
Final per-heuristic score for Nielsen Heuristic 2 (H2 Real-World Match). Derived from the LLM score with type coercion (and an n/a-aware path for H5/H9).
General Usefulness:
Traditional Ease of Automation:
Compare with other User fields.
Final per-heuristic score for Nielsen Heuristic 3 (H3 User Control). Derived from the LLM score with type coercion (and an n/a-aware path for H5/H9).
General Usefulness:
Traditional Ease of Automation:
Compare with other User fields.
Nielsen H4 Consistency
Final score for H4 Consistency, blending the LLM score 60% with the structural sub 40% via 3:2 weighting in avg(). The repetition trick bypasses Chimera's strict left-to-right evaluation without explicit decimal multiplication.
General Usefulness:
Traditional Ease of Automation:
Compare with other User fields.
Does the page prevent problems from happening in the first place? On pages with forms or user actions, look for clear labels, sensible defaults, required-field marking, and confirmation for destructive actions. Does not apply to purely informational pages.
General Usefulness:
Traditional Ease of Automation:
Compare with other User fields.
Nielsen H6 Recognition
Final per-heuristic score for Nielsen Heuristic 6 (H6 Recognition). Derived from the LLM score with type coercion (and an n/a-aware path for H5/H9).
General Usefulness:
Traditional Ease of Automation:
Compare with other User fields.
Nielsen H7 Flexibility
Final per-heuristic score for Nielsen Heuristic 7 (H7 Flexibility). Derived from the LLM score with type coercion (and an n/a-aware path for H5/H9).
General Usefulness:
Traditional Ease of Automation:
Compare with other User fields.
Nielsen H8 Aesthetic
Final per-heuristic score for Nielsen Heuristic 8 (H8 Aesthetic). Derived from the LLM score with type coercion (and an n/a-aware path for H5/H9).
General Usefulness:
Traditional Ease of Automation:
Compare with other User fields.
Final per-heuristic score for Nielsen Heuristic 9 (H9 Error Recovery). Derived from the LLM score with type coercion (and an n/a-aware path for H5/H9).
General Usefulness:
Traditional Ease of Automation:
Compare with other User fields.
Final per-heuristic score for Nielsen Heuristic 10 (H10 Help & Docs). Derived from the LLM score with type coercion (and an n/a-aware path for H5/H9).
General Usefulness:
Traditional Ease of Automation:
Compare with other User fields.
Nielsen Overall Score
Average of the 10 Nielsen per-heuristic scores. avg() skips real NULLs, so n/a paths on H5 and H9 (which materialize as NULL on float columns) do not drag the average down.
General Usefulness:
Traditional Ease of Automation:
Compare with other User fields.

Not showing supporting and helper fields. Show supporting and helper fields

Automation Notes

Several heuristics are hard to fully automate. Visibility of System Status and Aesthetic and Minimalist Design depend on visual rendering, motion, and feedback. Help Users Recognize, Diagnose, and Recover From Errors depends on what actually happens when something goes wrong — observable only by exercising the interface. Any automated approach will need to either approximate these from indirect signals or surface them for human review.

Error Prevention and Error Recovery do not apply to purely informational pages. Treating those as n/a rather than scoring them low, and skipping n/a values when averaging, keeps content pages from being unfairly penalized for not having forms.

Content-heavy sites tend to score consistently lower on Flexibility and Help & Documentation because the criteria are taken literally. If your site is informational by design, treat low scores on those two heuristics as expected rather than as defects.

For high-stakes evaluations, pair automation with human spot-checks on representative pages.

In Content Chimera

Chimera scores each page based on its text — rendered HTML stripped to plain text — so heuristics that depend on visual rendering or interactive behavior are inferred from text and structure rather than directly observed. A seeded language-model fieldset returns a 0-3 rating and a written rationale for each heuristic. For H4 Consistency, three XPath patterns (count of H1 tags, count of landmark regions, count of images missing alt text) are also extracted and blended with the language-model rating. The per-heuristic deliverables and the overall average are produced as calculated fields in the extent's flattened table.

The Run Now in Chimera button on this page launches the inventory-from-template skill, which copies the seeded fieldset and patterns into your extent, runs the summarize and extract pipelines, and creates the calculated fields automatically. You can optionally compose the Nielsen fieldset with an org-type baseline (minimal, higher_ed, research) or with E-E-A-T page analysis to capture additional dimensions in the same language-model call.