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Runn: bulk create/update actuals

runn_bulk_actuals

Create or update up to 100 actuals in one call, overwriting by project/person/role/date. Requires billable or non-billable minutes; if any invalid, none are written.

Instructions

Create or update up to 100 actuals in one call (POST /actuals/bulk). Each entry overwrites any existing actual for the same project/person/role/date. Either billableMinutes or nonbillableMinutes must be > 0. If any entry is invalid, none are written.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actualsYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.2.1

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description fully carries the behavioral burden. It discloses three critical non-obvious traits: overwrite semantics (same project/person/role/date), validation requirement (either billable or nonbillable minutes > 0), and atomicity (none written if any entry invalid). This is exemplary transparency.

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?

Three concise sentences deliver purpose, behavior, and validation without any filler. The most important information is front-loaded, and each sentence earns its place.

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?

For a tool with a nested array schema and no output schema, the description covers the essential invocation semantics: limit, overwrite behavior, validation, and atomicity. It omits the response format or error handling, but the core operation is sufficiently described for an agent to select and invoke the tool correctly.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate. It adds the important validation rule and mentions the identifying fields (project/person/role/date), but does not explain all nested fields or required properties. The schema provides structure, but the description only partially fills the semantic gap.

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?

The description opens with a clear verb+resource statement ('Create or update up to 100 actuals') and specifies the endpoint (POST /actuals/bulk). It also distinguishes itself from sibling tools like runn_list_actuals by emphasizing the bulk write nature.

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

Usage Guidelines4/5

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

The description clearly implies when to use the tool (bulk operations) by mentioning 'in one call' and the 100-item limit, but it does not explicitly name alternatives or exclusions. The context is clear enough without explicit 'use when' statements.

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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