Optional. Exact keyword / full-text search over the user's past
messages. source (optional) restricts to one platform label as saved
(e.g. "ChatGPT", "Claude"). limit optional (default 10, max 25).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | ||
| source | No |
| Name | Required | Description | Default |
|---|---|---|---|
| error | No | ||
| inbox | No | ||
| message | No | ||
| results | No | ||
| instruction | No | ||
| upgrade_url | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds useful behavioral details beyond the annotations: it clarifies the search scope ('user's past messages'), the source restriction to platform labels, and the limit default/max. These details help an agent predict behavior without contradicting the safe readOnly/idempotent hints.
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?
The description is short and front-loads the core purpose before parameter details. The stray 'Optional.' at the beginning is unnecessary and slightly confusing, costing it a perfect score, but the rest is efficient and earns its place.
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?
The description covers scope and parameter semantics, and the output schema handles return values. However, it lacks guidance on choosing between search_keyword and search_semantic, and does not clarify exact matching behavior (e.g., phrase matching, substring, case sensitivity). Given the tool's simplicity, this is adequate but not complete for an agent to use it optimally.
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?
With 0% schema description coverage, the description compensates by explaining that `source` restricts to a platform label (with examples) and that `limit` defaults to 10 and maxes at 25. The `query` parameter is implicitly understood as the keyword/full-text search term, though additional details like case-sensitivity or matching semantics would strengthen it.
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 names a specific verb ('search') and resource ('the user's past messages'), and the qualifier 'Exact keyword / full-text' distinguishes it from the sibling search_semantic. Even without naming the sibling, the contrast is clear and an agent can separate the two intents.
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?
Usage context is implied by 'Exact keyword / full-text search' — an agent can infer it should be used when exact matches are desired rather than semantic similarity. However, the description does not explicitly say when to use this tool over search_semantic or recent_messages, nor does it mention any exclusions or when not to use it.
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.
Most tools map cleanly to distinct resource+action pairs: projects, tasks, skills, user rules, memory, and messaging are all clearly separated. The main ambiguity is update_task versus update_task_state, since update_task can also change state and plan_status, though the descriptions do point to the narrow intended use.
The naming is largely consistent verb_noun snake_case: create_project, update_skill, delete_task, list_projects, get_context, save_turn. Minor deviations include recent_messages lacking a verb, remove_user_rule versus delete_* style, and singular user_rule in mutations versus plural user_rules in listing.
With 27 tools, the server is over the typical well-scoped MCP range, even though it covers several domains. Some consolidation is possible, such as folding update_task_state into update_task and reducing the overlapping retrieval/search tools.
The tool set provides strong lifecycle coverage for projects, tasks, skills, and user rules, plus memory retrieval, agent messaging, and onboarding help. Minor gaps exist, like no standalone get_task or list_tasks and no explicit inbox listing, but get_project and get_context largely cover those needs.
