Carbon Tracking MCP

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Collate Project Sessions Energy

collate_project_sessions_energy

Aggregate total and per-session energy and CO2eq for each Claude Code chat in a project using local session logs, with everyday equivalents.

Instructions

Total + per-session energy and CO2eq for every Claude Code chat in the current project.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description
`provider`	Yes	Coding-agent provider these sessions belong to ('claude' or 'codex').
`sessions`	Yes	Per-session breakdown of request count and estimated energy.
`comparisons`	Yes	Everyday-activity equivalents for the total estimated CO2eq.
`project_dir`	Yes	Absolute path to the project's session-log directory that was scanned.
`session_count`	Yes	Number of sessions included in this total.
`estimated_kg_co2`	Yes	Estimated CO2-equivalent emissions for the total, in kilograms.
`total_estimated_kwh`	Yes	Total estimated energy across all included sessions, in kilowatt-hours.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 13, 2026

TDQS

B3.4/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It says nothing about read-only safety, computation cost over many sessions, or any limits, leaving real gaps for a tool that aggregates across an entire project.

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

Conciseness4/5

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

A single tight sentence with the measured quantities and scope front-loaded and no filler. The '+' shorthand for total-plus-per-session is slightly cryptic but compact.

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

Completeness4/5

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

An output schema exists, so return values need no explanation, and the description states the metrics and scope needed to invoke a zero-param tool. Only the sibling relationship and any cost caveat are absent.

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

Parameters4/5

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

The tool takes zero parameters, so there is no parameter semantics for the description to add. Baseline 4 applies per the scoring rule for 0-param tools.

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

Purpose4/5

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

States a specific verb (collate) and resource (project sessions energy/CO2eq) and clearly scopes it to 'every Claude Code chat in the current project'. The project-wide scope implicitly distinguishes it from the current_session_energy sibling, but the sibling is never named, so an agent must infer the contrast.

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

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The project-wide scope hints at when this is appropriate versus a single-session tool, but there is no explicit when-to-use, when-not-to-use, or named alternative. Usage is left to inference rather than stated.

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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