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Dayze — Life in Days + Notable People

by com.dayze

Log Event (calendar write)

log_event

MUTATES the authenticated user calendar. Use for non-food days — funeral, cremation, appointment, dinner, anything that is not a food log. Do not store this as a chat memory. Example (funeral tonight): log_event({ title: "Funeral service — Mr Goh Choo Taw", date: "2026-08-29", time: "8pm", location: "Multi Purpose Hall, Blk 661 Jurong West St 64", category: "funeral" }). Example (Sunday cremation): log_event({ title: "Cremation — Mr Goh Choo Taw", date: "2026-08-30", location: "Mandai Crematorium", category: "funeral" }). Required: title + event_date (YYYY-MM-DD; alias date). Optional: event_time (8pm or 20:00; alias time), end_date, end_time, location, description, category, external_url, people / with / person_ids. Unknown people names do not fail the write. Inserts public.events (user-scoped, private), optional event_people, then rebuilds life_state. Requires API key or OAuth with scope context. Share tokens cannot write. ($0.10; API key required)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventYesA Dayze calendar event record.
people_taggedYes
unresolved_peopleYes
life_state_rebuiltYes

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond annotations by disclosing mutation, side effects (rebuilds life_state, inserts event_people), authentication requirements, share-token limitation, and cost. This gives the agent real operational expectations that readOnly/destructive hints do not capture.

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?

Front-loaded with the most important behavioral signal and usage scoping. The examples are useful but the required/optional list partially repeats schema content. Still, every sentence carries functional value, so length is justified.

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

Completeness5/5

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

Covers mutation scope, when to use, data inserted, side effects, auth, cost, parameters, and examples. With an output schema present, nothing material is missing for an agent to invoke this tool correctly.

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 already documents all parameters at 100% coverage, so baseline is 3. The description adds value with concrete examples, required vs optional summary, alias clarification, and the non-obvious behavior that unknown people names do not fail the write.

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?

Uses specific verb 'MUTATES' with resource 'authenticated user calendar'. Clearly separates from food logging by pinning the tool to non-food days (funeral, cremation, appointment, dinner), distinguishing it from sibling log_food without requiring schema inspection.

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?

States use case explicitly ('non-food days') and exclusion ('anything that is not a food log'), plus process advice ('Do not store this as a chat memory'). It does not name the sibling alternative (log_food) directly, but the condition is obvious enough to make the intended routing clear.

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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TDQS

B3.2/5.0
Disambiguation3/5

Many tools have explicit 'prefer X' guidance and mostly target distinct resources, but get_money_between_people is literally an alias for get_person_transactions, get_context_pack and get_life_context overlap heavily, and upload_asset/upload_photo both upload and re-encode images. Detailed descriptions partially rescue it, but the agent still faces avoidable near-duplicates.

Naming Consistency4/5

The vast majority follow verb_noun snake_case conventions (get_, log_, update_, search_, delete_, add_, archive_, resolve_, etc.). Deviations like the notable_* family and verbose aliases such as get_money_between_people are internally consistent subdomain patterns rather than chaotic naming. No camelCase or mixed style conventions appear.

Tool Count1/5

At 71 tools this far exceeds the 50+ threshold for an extreme tool count. Each domain may have legitimate operations, but the sheer volume would make agent navigation and tool selection expensive. Many listing, search, and upload variants could be consolidated without losing functionality.

Completeness3/5

The set broadly covers calendar, food, people, inventory, money, travel, assets, photos, Gmail, memories, and notable-people lookup with mostly CRUD-style operations. Notable gaps include no delete_expense, no delete_person, and no direct food-diary listing/getter, so some lifecycles end in workarounds. Overall it is broad but not fully complete.

Resources