Verify an engine result's audit_sha256. Pass the prior result object as JSON; any changed amount, fact, rule step, or source digest fails.
| Name | Required | Description | Default |
|---|---|---|---|
| result_json | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that changes in amount, fact, rule step, or source digest cause failure, providing some behavioral insight. However, it does not mention return format, side effects, or whether it is idempotent. The output schema likely covers some of this, but description itself is moderately transparent.
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 two sentences, front-loads the action, and contains no superfluous words. Every sentence provides essential information.
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 tool's simplicity (one parameter, output schema exists), the description is fairly complete. It explains what to pass and the failure condition. Missing minor details like exact output on success, but output schema likely covers that.
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 0%, so the description must compensate. It adds that the parameter should be a JSON string of the prior result, but does not detail expected structure or fields. Parameter name 'result_json' already hints at JSON, so description adds minimal meaning beyond that.
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?
The description clearly states the tool's purpose: verifying audit_sha256 of an engine result. It uses a specific verb 'verify' and resource, and it clearly distinguishes from sibling tools which are about calculations, descriptions, or rule packs.
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 clear context on usage: pass the prior result object as JSON and that any change in specified fields causes failure. It implicitly tells when to use (after obtaining a prior result), but does not explicitly state when not to use or mention alternatives.
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.
Each tool has a distinct purpose: calculation, verification, listing credits, retrieving rules, and agent description. No overlapping functionality.
All tools follow a consistent verb_noun snake_case pattern (e.g., calculate_tax_credit, list_rule_packs), making the set predictable.
With 5 tools covering core workflows (calculation, verification, rule access, agent info), the count is well-scoped and each tool earns its place.
The tool surface covers the essential operations for a tax credit engine: calculating, verifying results, and exploring available credits and rules. No obvious gaps.