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carbon_roadmap

Read-only

Roadmap carbone — Gapup agent-payable C-suite expertise (SUSTAINABILITY). Returns a structured, audited deliverable. Reference case: Cas démo — Roadmap carbone. Inputs are validated server-side — send the documented case fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
focusNo
companyYes
perimeterYes
scope1SourcesNo
scope2SourcesYes
reductionTargetsNo
scope3ActivitiesNo

TDQS

C2.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare readOnlyHint=true and openWorldHint=true. The description adds no additional behavioral context, such as authentication requirements, rate limits, or what happens to existing data. It merely restates that it returns a deliverable, which is already implied by the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short (two sentences) but includes unnecessary jargon ('Gapup agent-payable C-suite expertise') that does not aid understanding. The second sentence about validation and reference case is useful but could be more concise. Overall adequate but not efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (8 parameters, nested objects, no output schema), the description is severely lacking. It does not mention return format, output structure, or any examples. The absence of output schema increases the need for description completeness, which is not met.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 13%, yet the description provides zero explanation of parameters or their meaning. It only says 'send the documented case fields,' which adds no value. The parameters are complex nested objects, and without description assistance, agents cannot understand usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states it 'returns a structured, audited deliverable' related to a carbon roadmap, but lacks a clear verb-resource pairing (e.g., 'Generates a carbon reduction roadmap'). The jargon 'Gapup agent-payable C-suite expertise' obscures the purpose. Among sibling tools like 'carbon_footprint_calculator' and 'sustainability_report', this description does not differentiate clearly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 versus alternatives. The description mentions input validation and a reference case but does not specify when it is appropriate or not appropriate to invoke this tool compared to siblings.

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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TDQS

C2.5/5.0
Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

Resources