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Video: house rules, standing preferences (beta)

video_rules

House rules: this account's standing preferences for every video, in the user's own words, one per line (max 40). action=list shows them numbered; action=add (rule or rules[]) saves a new one; action=remove (which: number, numbers or the text) drops one; action=replace (rules[]) rewrites the set. Read them from video_guide at the start of a project and apply them without being asked. Offer to add one when the user corrects something they would want every time; send only with their go-ahead.

Input Schema

NameRequiredDescriptionDefault
ruleNoOne rule to add, or the text of one to remove.
rulesNoSeveral rules (add) or the whole set (replace).
whichNoremove: a 1-based number, a list of numbers, or the rule text.
actionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false), it discloses the 40-rule cap and that replace 'rewrites the set' wholesale while remove 'drops one' — the key risk differentiators between the two mutation actions. It stops short of saying whether removals are reversible or what add/remove return.

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?

Purpose is front-loaded in the first clause, then each action clause earns its place by carrying parameter or safety meaning. It is a dense single paragraph though, and the behavioral advice at the end could be split for scanability.

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?

With no output schema, the description covers the list return shape ('shows them numbered') and the cap on stored rules, which is what an agent needs to reason about state. What add/remove/replace return is left unstated, a minor gap for a small stateful tool.

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?

The description maps parameters to actions more explicitly than the schema does: rule or rules[] for add, which accepts a number, numbers, or the rule text for remove, rules[] for replace. That resolves the ambiguity of a polymorphic 'which' field and the dual-purpose 'rule' field. Only the action enum itself lacks a per-value gloss beyond the inline listing.

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?

Nails the resource (this account's standing video preferences), the storage shape (one per line, max 40), and the CRUD surface via named actions. It also positions itself against the sibling video_guide, which is where the rules are read from.

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?

Gives explicit when-to-use ('Read them from video_guide at the start of a project and apply them without being asked') and a when-to-write trigger ('Offer to add one when the user corrects something they would want every time; send only with their go-ahead'). It also states the consent gate, which is a real usage constraint rather than generic advice.

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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