Mark a follow-up / action done. Get the action_id from get_person (relationship.actions).
| Name | Required | Description | Default |
|---|---|---|---|
| action_id | Yes | The action to complete. |
| Name | Required | Description | Default |
|---|---|---|---|
| ok | Yes | Whether noticed completed the operation. | |
| data | No | The operation result when ok is true. | |
| error | No | A human-readable error when ok is false. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "http://json-schema.org/draft-07/schema#",
+ "additionalProperties": true,
+ "properties": {
+ "data": {
+ "additionalProperties": true,
+ "description": "The operation result when ok is true.",
+ "properties": {
+ "completed": {
+ "type": "boolean"
+ }
+ },
+ "required": [
+ "completed"
+ ],
+ "type": "object"
+ },
+ "error": {
+ "description": "A human-readable error when ok is false.",
+ "type": "string"
+ },
+ "ok": {
+ "description": "Whether noticed completed the operation.",
+ "type": "boolean"
+ }
+ },
+ "required": [
+ "ok"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description aligns with the annotations (readOnlyHint=false, idempotentHint=true) without contradiction. It does not add extra detail about side effects or idempotency beyond what annotations already convey, but the action is simple and well-covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, directly stating the purpose and providing a source for the parameter. No fluff or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter action, the description is complete. It covers what to do and where to get the ID. No output schema is given, so return values need not be explained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only says 'The action to complete', but the description adds valuable context: 'Get the action_id from get_person (relationship.actions)'. This enriches the parameter meaning significantly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'mark' and the resource 'follow-up / action done', making the tool's purpose unambiguous. It distinguishes itself from siblings like update_action and delete_action by focusing on the 'complete' action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a specific usage hint: 'Get the action_id from get_person (relationship.actions)', guiding where to source the ID. It does not explicitly contrast with alternatives like update_action, but the purpose is clear enough for typical use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.