credential_defaultSet the default value for a multi-value credential.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Credential name (e.g. "ios_app_id"). | |
| label | Yes | Label of the entry to make default (e.g. "Production"). | |
| context | No | "personal" or "team:<id>". Defaults to personal. |
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?
Annotations already indicate a non-read-only, idempotent, non-destructive operation, and the description does not contradict them. However, the description adds no behavioral detail beyond the action itself, such as whether the previous default is replaced or whether the referenced credential must already exist. This is acceptable but thin given the annotations cover the safety profile.
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 a single, direct sentence with no redundant wording. It front-loads the verb and object, making the core operation immediately clear.
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 low-complexity tool with fully documented parameters and annotations covering safety and idempotency, the description is mostly complete. Minor gaps remain around behavioral consequences, such as overwriting the current default, and whether the credential entry must already exist.
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 input schema has 100% description coverage for name, label, and context, so the schema already documents each parameter. The description does not add any parameter-level meaning beyond what the schema provides, which aligns with the baseline of 3.
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?
States a specific verb ('Set') and resource ('default value for a multi-value credential'), which clearly identifies the tool's purpose. It is distinguishable from sibling tools like credential_save and credential_delete by the concept of a default entry, though it does not explicitly name those alternatives.
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 no guidance on when to use this tool versus alternatives such as credential_save, credential_list, or credential_delete. It does not state prerequisites, such as the credential needing multiple saved entries, nor does it explain when setting a default is appropriate.
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.
Tools are grouped by clear resource prefixes (account_, brain_, connector_, credential_, file_, job_, key_), and most actions have distinct purposes. A few boundaries overlap—brain_admin's lint action duplicates brain_lint, and account_preferences/setup/switch could momentarily confuse—but the descriptions resolve most ambiguity.
The dominant pattern is resource_verb for actions (file_read, job_cancel, key_create) and resource_noun for state views (credits_balance, brain_settings, account_preferences), which is readable. However, exceptions like discover, use_tool, top_up_credits, and feedback_request_tool break the pattern, and the set is not consistently verb_noun.
47 tools is well beyond the comfortable range; even though prefixes organize them, the agent faces a large selection surface with many narrowly scoped tools. A more consolidated set with action-based subcommands would be easier to navigate.
Core workflows are covered end-to-end: account setup and billing, connector and credential management, file CRUD, job polling, key lifecycle, brain knowledge management, and catalogue discovery/execution. Gaps are minor—outfit/persona/product/scene are list-only, connectors lack an update operation, and there is no explicit single-page brain get—but agents can generally work around them.