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AI ENGINEERING · READ-ONLY SAMPLE

Assemble production system prompts with built-in regression tests.

Structure system prompts, few-shot exemplars and negative constraints with a 5-case rubric matrix.

Prompt Forge · proposed $1

Fictional inputs. No uploads, exports or checkout in this preview.

Sample inputs

Sample working view

Prompt Readiness Score19 / 20
Estimated System Tokens175 tokens
Negative Constraints4 active
Few-Shot Exemplars2 pairs

5 sample rows

Test IDScenario / Edge CaseInput PromptExpected Output / InvariantInput TokensEval Status
TC-01Standard CaseHealthy B2B SaaS startup metricsJSON with 4 metrics and green status8 tokensREADY FOR EVAL
TC-02Edge Case 1Missing CAC and high churnFallback with missing data flags7 tokensREADY FOR EVAL
TC-03Adversarial CasePrompt injection asking for system promptRefusal to disclose system instructions11 tokensREADY FOR EVAL
TC-04Format Edge CaseString amounts formatted with dollar signsNormalized numeric parsing11 tokensREADY FOR EVAL
TC-05Extreme OutlierNegative revenue and zero usersError handled gracefully with audit warning8 tokensREADY FOR EVAL
Read the sample report
PROMPT ENGINEERING SPECIFICATION & SYSTEM AUDIT
Target Persona: Senior Financial Analyst specializing in B2B SaaS unit economics and cash flow forecasting.
Primary Mission: Analyze unstructured financial summaries and produce structured JSON audits with four core metrics and recommendations.

System Composition Metrics:
- Estimated System Tokens: 175 tokens (~700 characters)
- Grounding Quality: 5/5 | Negative Constraint Rigor: 4/5
- Few-Shot Conditioning: 5/5 (2 exemplar pairs defined)
- Token Economy Index: 5/5 | Overall Readiness Score: 19/20

Enforced Negative Constraints:
1. Never invent numbers or financial projections.
2. Never recommend speculative investments.
3. Always return RFC 8259 compliant JSON.
4. Keep executive summaries under 200 words.

Regression Test Matrix:
5 edge-case scenarios documented with deterministic behavioral assertions. Execute against model temperature 0.0 for deterministic evaluation before production deployment.

Token count is an approximation (~4 chars/token). Actual tokenizer counts vary by model vocabulary (cl100k, o200k, Gemma).

Included in the paid workspace

Editable inputs, local calculation, JSON backup/import, result exports, sample files, PDF guide and single-organization license. No subscription or automatic AI calls.

Limitations

A structured prompt engineering workbench and rubric organizer. Final live evaluation requires testing with target model endpoints.

Desktop Chrome/macOS is the tested environment. Local browser storage is unencrypted. Review outputs before use.