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Theme Journey Interests

theme_journey_interests

START of the '$100 → $120' journey after the principles: record what the user is into (tapped chips or typed words) and map each interest to the backtest-ranked tradable themes. Returns the matched themes with their measured numbers and the next question. Works for anonymous users. (no key needed)

Input Schema

NameRequiredDescriptionDefault
interestsYesWhat the user said they are into, e.g. ['space', 'AI power demand'].
asset_classNoStocks, crypto, or both (the user's choice; one class = one vehicle).
conversation_idNoconversation_id returned by an earlier theme_journey_* call (keeps an anonymous visitor's interests and basket together until they register).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.4/5.0
Behavior3/5

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

Annotations declare readOnlyHint=false and idempotentHint=false, and the description's 'record what the user is into' is consistent with a stateful write. It adds real context the annotations lack: anonymous support, no key needed, and that it returns the next question. It does not, however, say whether repeat calls duplicate state or how conversation_id ties calls together beyond what the schema already states.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single dense sentence pair with no filler, but the front-loaded '$100 → $120' journey jargon delays the actual action ('record what the user is into... map each interest'). The essential behavior should lead.

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 does the right job of saying what comes back: matched themes with their measured numbers plus the next question. Combined with anonymous-user and no-key notes, an agent has enough to invoke it correctly; only call sequencing to siblings is left implicit.

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 coverage is 100%, so all three parameters are already documented in the schema, including the conversation_id continuity note. The description adds only mild value by reframing 'interests' as 'tapped chips or typed words', which clarifies input source but not format. Baseline 3 applies.

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 action set: record user interests and map each to backtest-ranked tradable themes, and positions it as the START step of the theme_journey_* sequence, which distinguishes it from siblings like theme_journey_subthemes or theme_journey_basket. The '$100 → $120' framing is decorative rather than informative, but the verb+resource is unambiguous.

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?

It implies ordering ('START of the journey after the principles') and notes it works for anonymous users with no key, which is useful context. However, it never explicitly says when NOT to call it or names which sibling to call next (subthemes, backtest, basket), leaving the sequencing to inference.

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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