Prompt Scoring | Smallest AI Docs

Prompt Scoring analyses your agent’s system prompt across 11 quality dimensions and returns an overall score (0–100), a grade, and actionable feedback for each dimension. Use it to catch weak spots before you go live.

Location: Agent editor → Prompt tab → score badge at the bottom of the editor

Seeing Your Score

When you open the Prompt tab of any single-prompt agent, the editor shows a score badge at the bottom of the prompt area. A coloured label — Strong prompt, Good prompt, Weak prompt, or Poor prompt — tells you the current grade at a glance.

Weak prompt badge with View issues link — Weak prompt badge in the agent editor — click 'View issues' to open the analysis panel.

Click View issues to open the Prompt Analysis side panel.

The Analysis Panel

The panel breaks down your score into individual dimension cards. Each card shows the dimension name, its quality level, and a quoted excerpt from your prompt as evidence.

Prompt analysis panel showing the overall score, latency estimate, and per-dimension findings.

Panel field	What it means
Overall grade	Numeric score (0–100) and label — Excellent / Good / Needs Work / Poor
First token latency	Estimated TTFT overhead added by your prompt length
Weak prompt / Strong prompt	Summary label derived from the overall score
Low / Normal / High latency	Token-density band for the current prompt

How Scoring Works

Each time you request a score, Atoms sends your prompt through two sequential Gemini passes — a Platform Analyst pass and a Rubric Judge pass — and returns scores for 11 dimensions grouped into three priority tiers.

Tiers and dimensions

Tier 1 — Core (highest priority)

Tier 2 — Quality

Tier 3 — Integrity (gating)

Dimension	What is checked
Role & Objective	Is the agent’s purpose and scope clearly defined?
Personality & Voice	Are tone and style specified with concrete guidance, not just adjectives?
Conversation Structure	Are there explicit flow phases and exit criteria?
Tool Integration	Are all referenced tools declared, with failure paths covered?
Constraints & Safety	Are safety rules, escalation paths, and hard limits spelled out?

Each dimension is rated Strong, Adequate, Weak, Missing, or Not Applicable.

Quality Levels and Token Bands

Grade thresholds

Score	Grade
90–100	Excellent
75–89	Good
50–74	Needs Work
0–49	Poor

Token density bands

The First token latency estimate and the density band are derived from your prompt’s token count.

Band	Token range	Latency impact
Lean	Fewer than 4K tokens	Very low
Normal	4K–9.9K tokens	Low
Heavy	10K–14.9K tokens	Moderate
Overweight	15K or more tokens	High

For voice agents, aim for the Normal band. Heavy and Overweight prompts increase first-token latency, which makes responses feel slower to callers.

Scoring via API

You can trigger scoring programmatically against a published version or a draft. Each call deducts 1 credit. Re-submitting an unchanged prompt returns a 400 — retrieve the cached result via GET /agent/{id} instead.

$ # Score a published version
$ curl -X POST https://api.smallest.ai/atoms/v1/prompt-scoring/score \
>   -H "Authorization: Bearer $SMALLEST_API_KEY" \
>   -H "Content-Type: application/json" \
>   -d '{"versionId": "6a1589b75e048394eb37bc47"}'
$ 
$ # Score a draft
$ curl -X POST https://api.smallest.ai/atoms/v1/prompt-scoring/score \
>   -H "Authorization: Bearer $SMALLEST_API_KEY" \
>   -H "Content-Type: application/json" \
>   -d '{"draftId": "6a1589b75e048394eb37bc48"}'

The response includes overall_score, overall_grade, band, estimated_ttft_overhead_ms, and a dimensions array with one entry per scored dimension.

Prompt scoring is only supported for single-prompt agents. Conversational flow (workflow-graph) agents return a 400.

→ Full API reference

Writing Prompts

Best practices for structuring your system prompt

Agent Versioning

Publish and manage agent versions safely