Estimate voluntary-market offset cost (USD) and tree- / forest-year equivalents for a given kg CO2e, using published constants. Pure compute; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| kgCO2e | Yes | Emissions to offset, in kg CO2e (>= 0) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It explicitly states 'Pure compute; price 0.0 (free)', which discloses key behavioral traits (no side effects, no cost). However, it does not mention rate limits or potential data sources, but for a simple compute tool, this is sufficient.
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, each providing essential information. It is front-loaded with the main action and resource, and every sentence earns its place. No superfluous words.
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 should clarify return values. It mentions 'offset cost (USD) and tree- / forest-year equivalents', which adequately informs the agent of the output types. However, it could be more explicit about the exact structure (e.g., numeric values, possibly an object). Still, it is reasonably complete for a simple compute tool.
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% for the single parameter 'kgCO2e', with a clear description. The tool description adds value by explaining what the output will be (offset cost and equivalents), but does not elaborate on the parameter beyond the schema. Baseline 3 is appropriate.
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 estimates voluntary-market offset cost and tree/forest-year equivalents for a given kg CO2e. The verb 'estimate' and resource 'offset cost' are specific, and it naturally distinguishes from sibling tools like carbon_estimate_compute_emissions which compute emissions.
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 implies usage by stating 'for a given kg CO2e' but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. The 'Pure compute; price 0.0 (free)' note gives some context but is not enough for clear usage differentiation.
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.