Export audit events from the live gateway. Supports JSON and CSV formats with date range filtering for SIEM integration.
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | Output format: ndjson or csv | ndjson |
| end_date | No | End date ISO format | |
| workspace | No | Workspace identifier | default |
| start_date | No | Start date ISO format |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by specifying the data source ('live gateway'), supported formats, and date-range filtering, but does not disclose potential size limits, pagination, or other operational nuances.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence with the primary verb and object upfront. Every phrase earns its place: 'live gateway' indicates source, 'JSON and CSV' indicates formats, and 'SIEM integration' indicates use case.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low tool complexity, complete 100% schema parameter coverage, and presence of an output schema, the description is largely sufficient. It clearly states purpose and context, though a brief mention of output size or time-range limits would make it fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters (format, start_date, end_date, workspace). The description reinforces the date-range filtering and format choice but does not add significant meaning beyond the schema fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action ('Export audit events'), the resource ('live gateway'), and the scope ('date range filtering for SIEM integration'). This distinguishes it from sibling tools like thinkneo_a2a_audit or thinkneo_get_observability_dashboard, which are not explicitly export-focused.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives context ('for SIEM integration') that implies when to use the tool, but it does not explicitly state when to prefer this over alternatives or mention any exclusions. Sibling tools suggest related audit/log capabilities, but no direct comparison is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping purposes, such as the multiple safety-check tools (thinkneo_check, thinkneo_detect_injection, thinkneo_evaluate_guardrail) and the many cost/reporting tools (thinkneo_agent_roi, thinkneo_decision_cost, thinkneo_business_impact). An agent would struggle to reliably pick the correct tool for a given intent. The boundaries between dashboard, audit, and reporting tools are particularly fuzzy.
All tools share the thinkneo_ prefix, but the remaining naming is inconsistent: some follow verb_noun (check_spend, list_alerts), some use noun_verb (compliance_generate, alert_rule_create), and others are bare nouns (business_impact, cache_status). This mix makes it hard to predict tool names based on action and object.
With 68 tools, this is an extremely large surface area, far beyond the typical 3-15 well-scoped set and even beyond the 25+ heavy threshold. Even for a comprehensive enterprise platform, the sheer number overwhelms an agent's ability to choose effectively. It feels like a kitchen-sink approach rather than a curated toolkit.
The toolset covers a wide range of governance, observability, and cost-management features, but there are notable lifecycle gaps: SLAs can be defined but not updated or deleted, alert rules lack an update operation, and registry entries have no remove/unpublish. Also, policy management is limited to checking, with no create/update tool. The memory tools feel out of place and lack a delete operation.
