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Update Trend Research Automation

update_trend_research_automation
Idempotent

Explicit two-phase write; never infer or default configurable values. Timezone is not an update input; the stored timezone is shown in the preview and preserved. Supply automation_id and at least one explicit changed value; untouched stored values are preserved and are not re-asked. A complete call without confirmation_token only previews the full resulting configuration and changed fields; repeat the identical call with the token after later user confirmation to write.

Input Schema

NameRequiredDescriptionDefault
uidNoOptional Firebase uid. Must match the URL uid unless local fallback is enabled.
topicNo
weekdayNo
platformNo
frequencyNo
daily_timeNo
bearer_tokenNoOptional Firebase ID token. Hosted clients normally authenticate with an API key in the Authorization header or ?uid= in the URL instead.
day_of_monthNo
automation_idNo
conversation_idNoCreator-list key for durable state. Reuse a returned list_id for follow-ups; when omitted, MCP uses the active generated list for this tool chain.
recipient_emailNo
preferences_modeNoHow to apply preferences for this call: 'stored' uses users/{uid}.agentPreferences, 'override' uses agent_preferences only, and 'none' disables stored filtering for this run.
agent_preferencesNoOptional per-call filtering preferences. Use with preferences_mode='override'. For backwards compatibility, passing this without preferences_mode implies override.
use_account_emailNo
confirmation_tokenNoShort-lived token from an identical complete preview. Supply only after the user confirms in a later turn.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing the two-phase preview/write contract, that a tokenless call mutates nothing and returns the full resulting config plus changed fields, that untouched values are preserved, and that timezone is preserved rather than updatable. This is exactly the mutation-safety context annotations alone cannot convey, and it is consistent with idempotentHint=true.

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?

Four dense sentences, front-loaded with the two-phase constraint, and every sentence adds an operative rule (no inference, timezone handling, minimum change, preview/token flow). No filler.

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 15-param mutation with no output schema, the description nails the safety-critical flow and the preservation semantics. It stops short of characterizing the domain fields the agent must actually set, so it is strong but not fully complete.

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?

With only 40% schema coverage across 15 params, the description carries real weight: it explains automation_id, confirmation_token, the 'at least one changed value' rule, and the non-parameter status of timezone. However, the majority of parameters (topic, weekday, platform, frequency, daily_time, day_of_month, recipient_email, use_account_email, uid) get no semantic help in the description, leaving a substantial gap.

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 states a specific verb+resource ('explicit two-phase write' of a trend research automation's configuration) and makes the preview-then-write nature unambiguous. It never explicitly says what resource is being updated (only 'configurable values' and 'resulting configuration'), and it does not distinguish itself from the sibling update_automation, so a 4 is right.

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?

Clear when-to-use rules: supply automation_id plus at least one explicit changed value, never infer or default values, and only pass confirmation_token after later user confirmation. It gives no guidance on when to choose this over the closely named update_automation sibling, which keeps it from 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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