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Prune previewed Micro records

micro_retention_prune
Destructive

Permanently remove aged project records after confirming the exact previewed count. Fails safely if policy or eligible records change, never affecting purchases or entitlements.

Instructions

Permanently prune the exact currently previewed count of aged project records. Fails if policy or eligible records changed; never affects purchases or entitlements.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoMicro project directory; defaults to the server working directory
confirmYesExplicit confirmation that the exact previewed record count should be permanently pruned
expectedRecordsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
jsonNo
stderrYes
stdoutYes
commandYes
exitCodeYes
Install Server

TDQS

A4.2/5.0
Behavior5/5

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

Annotations already mark this as destructive and non-idempotent, and the description meaningfully adds that the operation is permanent, fails on any policy/record change, and never touches purchases or entitlements. This gives the agent strong expectations about side effects, failure modes, and safety boundaries.

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?

Two sentences, front-loaded with the core operation, and every clause earns its place: permanence, exact count, failure condition, and side-effect exclusion. No repetitive or boilerplate language.

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?

For a destructive mutation tool, the description covers what is being pruned, the count exactness, when it fails, and what it will never affect. An output schema exists, so return-value details are unnecessary. The description is sufficient to call the tool safely.

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 67%, and the description compensates for the undocumented expectedRecords by identifying it as the 'exact currently previewed count'. It also reinforces the confirm parameter's destructive-confirmation semantics, though it does not describe path behavior beyond the schema.

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?

The description clearly identifies the action ('permanently prune'), the resource ('ged project records'), and a precise constraint ('exact currently previewed count'). It is distinguishable from sibling delete/retention tools by its preview-coupled count semantics, though it does not explicitly name an alternative.

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 description implies the intended use: run after previewing a retention count and only while the policy/eligible records are unchanged. It does not explicitly say when to prefer this over micro_record_delete or micro_project_delete, nor does it state exclusions, so usage guidance is implied rather than explicit.

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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