Agent Tool Calling Schema Diagnostic for Product Catalog Ingestion
Evaluate tool-calling JSON schema definitions and payload integrity for automated product listing ingestion agents.
Use this template when configuring or troubleshooting autonomous agents that parse vendor data into product listings. It pinpoints schema mismatches, missing required parameters, and execution failures in agent tool definitions.
Role: Senior E-Commerce Systems Architect specializing in autonomous tool-calling integrations.
Context
- Source catalog structure: {{catalog_source_format}}
- Ingestion agent tool schema: {{target_agent_tool}}
- Required listing attributes: {{listing_attribute_set}}
- Representative tool payload: {{payload_sample}}
- Error output log: {{validation_error_log}}
Task
Conduct an analysis of the agent tool-calling definition against incoming product listing data, producing an actionable diagnostic report that identifies schema incompatibilities, type coercion failures, and parameter omissions to ensure seamless automated catalog publishing.
Method
- Cross-reference the parameters in {{target_agent_tool}} against the mandated fields in {{listing_attribute_set}}.
- Inspect {{catalog_source_format}} to identify source properties that lack deterministic mapping in the agent tool schema.
- Evaluate {{payload_sample}} for nested object depth, scalar type accuracy, and array formatting violations.
- Correlate specific tracebacks in {{validation_error_log}} with parameter descriptions and required flags in the tool schema.
- Detect edge cases where ambiguous parameter naming causes the autonomous agent to hallucinate incorrect listing attributes.
- Formulate precise schema adjustments, including field descriptions, enums, and required properties.
- Provide corrected JSON schema snippets for the tool-calling definition.
Constraints
- MUST validate every attribute listed in {{listing_attribute_set}} against the tool parameters.
- MUST NOT suggest replacing structured tool calling with unstructured markdown generation.
- Analysis must focus strictly on JSON schema compliance and agent parameter extraction reliability.
- All schema corrections must comply with OpenAPI 3.0 / JSON Schema Draft 7 specifications.
Output format
1. Schema Diagnostic Summary
- High-level health status (Passing, Degraded, Critical)
- Root cause classification table (Type Mismatch, Missing Key, Ambiguous Description)
2. Attribute Mapping Analysis
- Itemized evaluation of mandatory listing fields versus agent tool arguments (3-5 key findings)
3. Error Trace Breakdown
- Line-by-line mapping of {{validation_error_log}} entries to specific agent failure points
4. Remediation Plan & Patched Schema
- Corrected tool-calling JSON schema definition (under 60 lines)
Self-review
- Did I verify every parameter in {{listing_attribute_set}} against {{target_agent_tool}}?
- Are the proposed schema modifications syntactically valid JSON Schema?
- Does the analysis directly address the exact errors documented in {{validation_error_log}}?
Explicit role, a named task, and discrete steps the model can follow.
Background, inputs and variables the model needs before it starts.
Hard boundaries — what the model must and must not do.
A named, field-level shape for the response.
Ordered work items that force analysis before an answer.
Length and structure that travel across frontier models.
Signal density — instruction weight without padding.
Documented variables so the scaffold adapts to new inputs.
Quality bar, assumptions and behaviour when inputs are thin.
How much real usage the template has behind it.