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Povver — Strength Training

Update Memory Status

update_memory_status
Idempotent

Update an injury memory's lifecycle status. Use 'resolved' when the user confirms an injury is fully gone. Use 'monitoring' for ambiguous cases (typically the pipeline auto-transitions). Use 'active' to revert if pain returns. Tagged with source='external_mcp' in the audit trail.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteYes
statusYes
memory_idYes
idempotency_keyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations provide idempotentHint=true and destructiveHint=false, and the description adds extra behavioral context: updates are tagged with source='external_mcp' in the audit trail, and monitoring status is normally auto-transitioned by the pipeline. This goes beyond the structured metadata without contradicting it.

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?

The description is compact and front-loaded with the primary action. Every sentence serves a purpose: stating the action, explaining the three status choices, and noting the audit trail behavior. There is no filler or repetition.

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 write operation with no output schema, the description covers the core decision space: which status to set, when each is appropriate, and a relevant audit side-effect. It does not mention the return value or the optional idempotency_key, but those are less critical given the annotations and schema.

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 description coverage is 0%, so the description must compensate for the parameters. It thoroughly explains the status enum's values and when to use each, which is the most semantically rich parameter. The remaining parameters (memory_id, note, idempotency_key) are left to their names and annotation context, which is acceptable but not fully elaborated.

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 specific verb and resource: 'Update an injury memory's lifecycle status.' It also names the exact statuses and their meanings, making the tool's purpose unmistakable and clearly distinct from generic update or memory retrieval siblings.

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 gives concrete guidance for each status value: 'resolved' when the injury is gone, 'monitoring' for ambiguous cases, and 'active' to revert if pain returns. It also warns that monitoring is 'typically the pipeline auto-transitions,' which helps the agent decide when manual intervention is appropriate. It does not explicitly contrast with siblings like save_injury_memory, so it falls short of a 5.

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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