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save_report

Save an analytics report for reuse. Give it a NAME plus the same measure / group_by (/ dimension_key / agreement_id) you'd pass to analyze — the governed spec is stored under that name (re-saving the same name updates it). Later, run_report re-runs it on current data. Requires a connected Aurgus account.

Input Schema

NameRequiredDescriptionDefault
nameYesA name to save this report under (e.g. 'Rebate by class').
measureYesaccrued | settled | basis | count.
group_byYesagreement | class (needs dimension_key) | month | quarter.
agreement_idNoOptional — restrict to one agreement.
dimension_keyNoRequired when group_by='class' — e.g. interchange_class.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations only declare it is a non-read, non-destructive write. The description adds the non-obvious upsert behavior ('re-saving the same name updates it'), that a governed spec is persisted, and the auth prerequisite — real value beyond structured fields. It stops short of saying what happens to a spec when an agreement/dimension is later removed, or error behavior on name collisions with different specs.

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

Conciseness5/5

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

Four short clauses, front-loaded with the action, then the payload, then the upsert caveat, then the downstream tool and prerequisite. No sentence is filler; the parenthetical enum hint is compact rather than redundant.

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

Completeness5/5

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

No output schema exists, but the description tells the agent what is stored, how it is keyed, how it is mutated, and how it is consumed later — enough to call it correctly and reason about consequences. Remaining unknowns (return payload shape) are low-stakes for a save operation.

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?

Schema coverage is 100%, so the baseline is 3; the description earns a notch by framing all fields as 'the same measure / group_by (/ dimension_key / agreement_id) you'd pass to analyze', giving the agent a way to derive correct values from a familiar call rather than reading the enum lists cold.

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

Purpose5/5

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

Opens with a specific verb + resource + purpose ('Save an analytics report for reuse') and immediately distinguishes itself from siblings by naming `analyze` (source of the spec) and `run_report` (later re-execution). An agent can place it in the lifecycle without opening another schema.

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

Usage Guidelines5/5

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

Explicitly states what to pass, that re-saving the same name updates rather than duplicates, that `run_report` is the follow-up, and the precondition of a connected Aurgus account. Effectively covers when-to-use and which sibling to reach for next.

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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