ghg-ledger
Server Details
Deterministic Scope 1/2/3 GHG inventories with bundled factors and audit hashes.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.7/5 across 6 of 6 tools scored. Lowest: 3.1/5.
Each tool has a clearly distinct purpose: inventory calculation, activity classification, agent description, factor pack retrieval, factor pack listing, and result verification. There is no overlap or ambiguity.
All tool names follow a consistent verb_noun pattern (e.g., calculate_inventory, classify_activity, verify_result), making the set predictable and easy to navigate.
With 6 tools, the server is well-scoped for its purpose—covering core operations like inventory calculation, classification, factor pack access, and verification without unnecessary bloat or deficiency.
The tool surface covers the primary workflows: calculating inventories, classifying activities, retrieving factor packs, listing available packs, and verifying results. A minor gap is the lack of tools for managing activity records directly, but they may be supplied externally.
Available Tools
6 toolscalculate_inventoryAInspect
Calculate an auditable GHG inventory from explicit activity records. Returns per-line gas/CO2e results, Scope 1/2/3 and category rollups, dual Scope 2 reporting, indeterminate lines, factor lineage, notary payload, and an offset-clearinghouse dry-run weave. This is calculation, not advice.
| Name | Required | Description | Default |
|---|---|---|---|
| options | No | ||
| activities | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It lists detailed output components (per-line results, rollups, etc.) and states 'auditable', which suggests reliability. However, it does not mention safety, auth needs, idempotency, or side effects, leaving gaps in behavioral transparency.
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 (actually two sentences plus a short phrase) that front-load the purpose and then list outputs efficiently. Every word earns its place with no filler 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?
Given the tool's complexity (GHG inventory calculation with many return components), the description covers the output thoroughly. An output schema exists, but the description still adds interpretive context (e.g., 'dual Scope 2 reporting', 'indeterminate lines'). However, input semantics are lacking, and no usage scenarios or prerequisites are provided.
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%, and the description only vaguely mentions 'explicit activity records' without explaining the format or required fields for the 'activities' parameter. The 'options' parameter is not addressed at all, so the description adds minimal semantic value beyond the bare schema.
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 'Calculate an auditable GHG inventory from explicit activity records', using a specific verb and resource. It distinguishes from sibling tools by adding 'This is calculation, not advice', which helps the agent differentiate from advisory tools like describe_agent.
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 for calculation of GHG inventories from explicit activity records, but does not explicitly state when to use or avoid this tool versus siblings. 'Not advice' is a weak exclusion, and no alternative tools are named or contrasted.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
classify_activityAInspect
Suggest scope and Scope 3 category from the bundled deterministic map. No inference is used; unknown activity types return no suggestion.
| Name | Required | Description | Default |
|---|---|---|---|
| activity | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses key behaviors: deterministic (no inference) and handling of unknown types (no suggestion). This adequately conveys the tool's traits, though it omits details like side effects or authentication requirements, which are less critical for a classification tool.
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 with two sentences: the first states the purpose, and the second adds a critical behavioral caveat. Every word adds value, and the information is front-loaded.
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 complexity (one parameter, no schema descriptions, but an output schema exists), the description covers the tool's core function and a key behavioral trait. However, it lacks documentation for the input parameter, which is a significant gap for a tool with an unstructured object parameter. The presence of an output schema mitigates the need for return value details, but the input remains underdocumented.
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 description adds no meaning to the 'activity' parameter beyond the schema, which only defines it as a required object with additional properties. With 0% schema description coverage, the description should explain what properties the activity object should contain, but it does not, leaving the agent to guess its structure.
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 suggests 'scope and Scope 3 category' from a deterministic map, with the specific verb 'suggest' and resource 'scope and Scope 3 category'. It distinguishes from siblings by emphasizing 'No inference is used', making the purpose unambiguous.
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 when to use: for classifying activities using a deterministic map. It notes that unknown activity types return no suggestion, but does not explicitly state when not to use or provide alternatives. The context is clear but not exhaustive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
describe_agentBInspect
Return fleet-standard capabilities, version, pack digest, and pricing.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose behavioral traits such as read-only nature, authentication needs, or potential side effects. Assumed safe but not explicit.
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?
Single sentence, no wasted words. Efficiently conveys the output. Could be slightly more structured but very concise.
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?
Tool has zero parameters and an output schema. Description adequately summarizes return fields but lacks context about prerequisites, side effects, or relationship to siblings. Adequate but not complete.
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?
No parameters exist (schema coverage 100%), so baseline is 3. Description adds meaning by listing what the return value includes (capabilities, version, pack digest, pricing), exceeding minimal schema info.
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 tool returns 'fleet-standard capabilities, version, pack digest, and pricing', which are specific resources. It distinguishes from siblings which involve inventory, classification, or factor pack operations.
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 guidance on when to use this tool over alternatives. Given siblings like get_factor_pack and list_factor_packs, the description does not clarify the context for choosing describe_agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_factor_packAInspect
Return factors, GWP values, conversions, sources, and pack SHA for one exact bundled region/year. No nearest-region or nearest-year substitution.
| Name | Required | Description | Default |
|---|---|---|---|
| year | Yes | ||
| region | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully bears the burden. It discloses key behaviors (strict matching, returned data types). It does not cover auth, rate limits, or error handling but is adequate for a read operation.
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 concise sentences with no wasted words. It front-loads the action and adds a critical constraint immediately.
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 (2 params, output schema exists), the description is fairly complete but could mention error handling for nonexistent packs. It covers core behavior and strictness.
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 0%, but the description adds meaning by clarifying that region and year are exact identifiers for a bundled pack and that no substitution occurs. It does not specify format or allowed values, but the strictness context is valuable.
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 returns factors, GWP values, conversions, sources, and pack SHA for an exact region/year bundle, distinguishing it from siblings like list_factor_packs that likely list multiple 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 explicitly says 'No nearest-region or nearest-year substitution', indicating when this tool should be used (exact matches). However, it does not mention when not to use or point to alternative tools for fuzzy matching.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_factor_packsAInspect
List the bundled pack version/digest, supported regions and years, activity types, GWP set, and explicit MVP coverage.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden. It discloses what info is returned but does not mention any behavioral traits like read-only nature, auth requirements, or potential side effects.
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?
Description is a single sentence that enumerates key items concisely, though slightly lengthy. No wasted words, but could be more structured.
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 parameters and an output schema, the description covers what the tool returns adequately. Could mention number of packs or update behavior, but not essential.
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?
With zero parameters, the description need not add meaning beyond schema. It adds value by explaining output content, meeting the baseline of 4.
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 verb 'List' and specifies exactly what is listed (pack version/digest, regions, years, activity types, GWP set, MVP coverage), differentiating it from siblings like get_factor_pack.
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 when-to-use or when-not-to-use guidance is provided. It is implied that this tool is for obtaining an overview, but it does not distinguish from get_factor_pack or other siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
verify_resultBInspect
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 |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It states it recomputes and flags tampering/stale lineage, but omits side effects, required permissions, error handling, or rate limits. The output format (what 'flagged' means) is unclear despite the presence of an output schema.
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 with no redundancy. The action and object are front-loaded. Every word contributes to understanding.
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 presence of an output schema, the description does not need to detail return values. However, it lacks context about when to verify, how to interpret the flagging, and the relationship with sibling tools. It is adequate but not thorough for a verification 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 coverage is 0%, so the description must compensate. It clarifies that 'result_json' should be a JSON representation of the prior result object, but does not specify the expected structure or keys. This adds basic meaning but leaves ambiguity for the AI agent.
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 verb 'recompute' and identifies the resource as 'a prior inventory's audit hash and conservation checks'. It implicitly distinguishes from sibling tools like calculate_inventory or get_factor_pack, which are not verification-focused. However, it does not explicitly differentiate or mention the workflow context.
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 no guidance on when to use this tool versus siblings. It implies it is for verifying prior results but does not state prerequisites, exclusions, or alternatives. The phrase 'pass the prior result object' hints at use after an inventory calculation, but without explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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