search_entries
Search timeline entries by text
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search term | |
| projectId | No | Restrict to one project (optional) |
USECREA
by com.usecrea
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
B3.1/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. It only states that it searches by text, but does not disclose matching behavior, result ordering, pagination, or whether the operation is read-only.
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 a single, focused sentence with no filler. It front-loads the action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter search tool, this is minimally adequate: the required query parameter and optional projectId are documented in the schema. However, the lack of return-format or behavior details prevents it from being 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?
Schema coverage is 100%, and both parameters have descriptions. The description adds minimal semantic value beyond restating that the search is by text and scoped to timeline entries, so the baseline of 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 clear verb ('Search'), a resource ('timeline entries'), and the mechanism ('by text'). It is distinguishable from siblings like list_entries and search_knowledge, though it does not explicitly name them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not explain when to use this tool over alternatives like list_entries, search_knowledge, or search_project, nor does it mention any exclusions or prerequisites.
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
B3/5.0
Disambiguation3/5
Most tools target distinct resources (elements, knowledge, tasks, datasets, snapshots), but a few pairs blur boundaries: create_project/init_project both create projects, and pin_knowledge/set_knowledge_relevance both mark importance for future agents. The descriptions help separate them, but misselection is possible without careful reading.
Naming Consistency3/5
Tool names consistently use snake_case verb_noun and have solid list_/get_/search_ conventions. However creation verbs are inconsistent (add_element vs create_entry vs save_dataset vs init_project), and deletion mixes delete_entry/delete_file with remove_element, making the naming pattern less predictable than it could be.
Tool Count2/5
48 tools is well above the typical well-scoped range, and the set includes many lifecycle variants (create/init/save/add, delete/remove, update/set) that inflate the count. While the server covers a broad domain, the sheer number makes it heavy and harder for an agent to navigate.
Completeness3/5
The core surfaces (projects, elements, knowledge, timeline, tasks, chats, datasets, snapshots, files) have solid create/read/update coverage, with search and session-handoff tools. Notable gaps exist: read_file references a download path for binary files that no tool provides, and there is no get_entry or delete/archive for projects, datasets, snapshots, or chat sessions.