Recompute a prior inventory's audit hash and conservation checks. Pass the prior result object as JSON; tampering or stale factor lineage is flagged.
| 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 provided, the description carries the full burden. It discloses the core behavior: recomputing hash, performing conservation checks, and flagging tampering/stale lineage. No side effects are mentioned, but 'recompute' implies a read-only verification, and the output schema covers return details.
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 well-structured sentences. The first sentence front-loads the main action, and the second adds usage and outcome details. No unnecessary words or redundancy.
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?
For a single-parameter tool with an output schema, the description covers the essential aspects: purpose, usage, and outcome. It does not explicitly mention relationship to calculate_inventory, but sibling context implies it. Overall, the description is sufficient for selecting and invoking the tool correctly.
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?
The schema has a single parameter with 0% description coverage, so the description must compensate. It adds meaning by specifying 'Pass the prior result object as JSON', clarifying that result_json should be a JSON serialization of a prior inventory result, which goes beyond the bare parameter name.
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 specific action: 'Recompute a prior inventory's audit hash and conservation checks.' It distinguishes itself from sibling tools like calculate_inventory and classify_activity by focusing on verification of an existing result rather than creating or classifying.
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 provides clear usage context: pass the prior result object as JSON, with outcomes of flagging tampering or stale factor lineage. It does not explicitly name alternatives or exclusions, but the context is unambiguous for verification tasks.
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 targets a distinct action: calculate, classify, describe, get, list, and verify. There is no overlap or ambiguity between the tools.
All tool names follow a consistent verb_noun pattern in lowercase snake_case, making the API predictable and easy to navigate.
The server has 6 tools, which is well-scoped for its purpose of GHG inventory calculation and verification. Each tool serves a clear role without redundancy.
The tool set covers the core workflows: calculating inventories, classifying activities, retrieving factor packs, listing available packs, and verifying results. No obvious gaps are present for the stated domain.