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Glama

noticed

by so.noticed.mcp

sync_connected_source

After explicit user confirmation, request a fresh import for one connected noticed source. This queues work and never means the import is already complete. It does not send anything through the provider.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYesConnected integration source to refresh.
confirmedYesSet to true only after the user explicitly confirms this sync.
account_idNoAccount id from source status; required for multi-account sources.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesWhether noticed completed the operation.
dataNoThe operation result when ok is true.
errorNoA human-readable error when ok is false.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

The description discloses important behavior beyond the annotations: it queues work asynchronously, does not imply completion, requires explicit user confirmation, and does not send anything through the provider. These are non-obvious traits that help an agent avoid incorrect assumptions about a sync operation.

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?

The description is three short sentences, each earning its place: action and requirement, async/completion semantics, and negative behavior. It is front-loaded with the most important condition and contains no redundant 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?

The description covers the key operational facts: confirmation, queuing, non-completion, and no provider send. With a full input schema and an output schema present, this is nearly complete, though naming get_connected_source_status for checking sync completion would make it even stronger.

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 100%, so the parameters are already well documented. The description adds confidence around the confirmed parameter and the meaning of 'source', but it does not need to add more since the schema carries the parameter-level detail.

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?

The description names a specific action ('request a fresh import'), a clear resource ('one connected source'), and distinguishes itself by stating it queues work and never means the import is complete. This clearly separates it from related tools like get_connected_source_status.

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?

The description explicitly conditions use on explicit user confirmation, which matches the confirmed const true parameter. It does not explicitly name sibling alternatives for checking status or connection setup, but the usage context is otherwise 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

B3.4/5.0
Disambiguation3/5

The tool set is organized around distinct resources, and the descriptions work hard to separate them, but several close pairs remain easy to confuse: add_memory vs memory_save vs add_note, accept_identity_match vs suggest_identity_match, and dismiss_identity_match vs mark_different_people. An agent will often need to read very subtle signals (who originated the content, pending vs initiating a merge, soft vs durable rejection) to pick the right tool.

Naming Consistency3/5

Most tools follow a clear verb_noun snake_case pattern like create_list, update_person, and delete_view, which is readable and mostly predictable. However, the memory tools break the pattern (memory_save, memory_get, memory_search instead of save_memory/get_memory/search_memory), and a few noun-style names (my_profile, network_summary, account_status) add inconsistency.

Tool Count1/5

At 57 tools, this is an extremely large surface that exceeds the calibration threshold for an extreme mismatch. The scope is broad, but many tools are micro-specialized variations of the same concept, such as four memory-related tools and seven identity-match tools, which makes the count feel inflated rather than well-scoped.

Completeness4/5

The tool set provides thorough lifecycle coverage for the core domain: people can be added, updated, searched, and removed; lists, views, actions, and scheduled tasks have create/read/update/delete; and identity matching has accept, dismiss, differentiate, and suggest paths. Minor gaps exist, such as no direct memory/note deletion or intro deletion, but agents can generally complete workflows without hitting dead ends.

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