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update_fact

Destructive

Change ONE fact — its text, its horizon, its date, its tags. Use it when the athlete corrects something or when a horizon is answered ("tennis holds through the winter" → move the recheck). A card, because this edits something already on their Profile page and often something they wrote — except rewriting their existing "Language:" fact when they ask to switch language, which saves on return. To only bump a pattern's strength use confirm_fact, which is silent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
areaNo
tagsNo
textNo
dueDateNo
horizonNo
dueLabelNo
seasonToNo
dueActionNo
seasonFromNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already carry destructiveHint=true and readOnlyHint=false, so the description doesn't need to restate the mutation. It adds context that this edits existing Profile content and calls out a special Language-fact case that 'saves on return,' but it does not disclose response behavior or whether changes are reversible.

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?

The core action is front-loaded and each sentence adds usage value. The phrase 'A card, because...' and 'saves on return' are slightly jargon-y and could confuse an agent without product context, but overall the description is appropriately sized.

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

Completeness3/5

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

For a destructive 10-parameter tool with no output schema, the description covers the main use cases and the key alternative. It is not complete enough for confident use of the more specialized params (area, season fields, dueAction/dueLabel) or to know what a successful update returns.

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 names text, horizon, date, and tags, and the horizon-answered example gives useful meaning to recheck-style updates. However, it omits area, dueAction, dueLabel, seasonFrom, and seasonTo, and doesn't clarify that id is the only required field with the rest being optional partial-update fields.

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?

States a specific verb and resource ('Change ONE fact') and names the editable parts: text, horizon, date, tags. It differentiates from confirm_fact by contrasting silent pattern-strength bumps with this editing action, so an agent can distinguish it from siblings.

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 gives trigger conditions: when an athlete corrects something or when a horizon is answered, including a concrete example. It also names confirm_fact as the alternative when only pattern strength needs bumping, giving clear routing guidance.

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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