Look up the published emission factor (value, unit, category) for a named activity key (e.g. shipping_air, electricity_global, travel_car, gasoline, beef). Pure compute; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| activity | Yes | Canonical activity key (e.g. shipping_air, travel_car, gasoline) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must fully disclose behavior. It states the tool is 'pure compute' and free, but omits details on error handling for invalid activity keys, authentication requirements, or rate limits. The behavioral disclosure is minimal.
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 extremely concise—two sentences with no filler. It front-loads the action ('Look up the published emission factor') and efficiently provides examples and pricing.
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 no output schema, the description mentions the return fields (value, unit, category) but does not elaborate on the response structure. For a simple lookup tool, this is adequate but could be more informative about expected output format.
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 coverage is 100% with the activity parameter already described as a canonical key. The tool description adds extra examples (beef, electricity_global) beyond the schema, providing additional context for valid values.
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: looking up published emission factors for a named activity key. It provides specific examples (shipping_air, electricity_global, etc.) and distinguishes itself from sibling tools like carbon_estimate_compute_emissions by focusing on a single factor lookup.
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?
No explicit guidance on when to use this tool over alternatives. While it mentions 'Pure compute; price 0.0 (free)', it does not describe when to choose this vs. other carbon estimation tools (e.g., compute_emissions, offset_estimate).
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.
Most tools have clearly distinct purposes, especially the ledger-watch groups with domain prefixes. However, there are near-duplicate utilities such as content_authenticity_domain_reputation and domain_intel_reputation, and fx_tax_convert overlaps with price_oracle_fx_rate/convert. The sheer number of tools also increases the chance of selecting the wrong one, though descriptions are generally clear.
The naming is largely consistent with a <domain>_<action> or <domain>_<watch>_<action> pattern, and all names use snake_case. Minor deviations include standalone names like entity_search, kyb_report, verify_receipt, and the confusing singular/plural pair of sanction_watch_* and sanctions_screen_*. Overall, the pattern is predictable.
With 172 tools, this server is far beyond the typical well-scoped range. It bundles dozens of unrelated utility domains (weather, carbon, CVE, geo, etc.) alongside the Japan public-ledger watches, making it unwieldy for an agent to navigate. This extreme count is a major coherence problem.
For the core Japan public-ledger domain, coverage is excellent: each ledger has search, get, timeline, recent_changes, and verify_ledger, plus cross-ledger entity_search and temporal_query. The unrelated utility areas are also fairly complete for their own purposes, but the server's scope is so broad that some utilities are duplicated (e.g., multiple currency converters). Overall, no critical dead ends in the main domain.