create_key
POST /v1/agent/keys — mint another key. Does NOT add USDC credit. Plaintext shown once.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Label for the new API key |
POST /v1/agent/keys — mint another key. Does NOT add USDC credit. Plaintext shown once.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Label for the new API key |
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 are minimal (only hint flags), so the description carries the behavioral burden. It adds useful non-obvious facts: no USDC credit is added, and the plaintext key is shown only once. This meaningfully helps the agent avoid misusing the tool, though it could say more about side effects or persistence.
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 extremely compact: endpoint, purpose, a pricing/funding caveat, and a security-relevant warning in just three short clauses. Every fragment adds value, and the most important action is front-loaded.
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 single-parameter creation tool with no output schema, the description is nearly complete: it names the endpoint, states the key's one-time plaintext visibility, and clarifies the funding limitation. It doesn't explain what happens on duplicate names or other error cases, but those are minor given the tool's simplicity.
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 already documents the single parameter 'name' with a clear description, and schema description coverage is 100%. The tool description adds no additional parameter-level detail, so the baseline score of 3 is appropriate.
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 uses a specific verb ("mint") and resource ("another key") and even gives the exact endpoint, making the tool's function unmistakable. It also distinguishes itself from sibling tools like list_keys and revoke_key by positioning itself as a key creation operation.
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 clearly implies use when the agent needs to create a new API key, and it explicitly states a when-not: this tool does NOT add USDC credit. However, it does not name an alternative tool for adding credit, so it stops short of the explicit cross-referencing that would earn a 5.
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.
Several video tools are effectively duplicates: generate_video and video_queue both target POST /v1/video/queue, while get_generation_status and video_retrieve both call POST /v1/video/retrieve. The non-video tools are distinct, but these overlapping boundaries make it hard for an agent to choose the correct variant.
Tool names are uniformly snake_case and many follow a verb_noun pattern such as create_key, list_keys, and get_models. However, the video tools use an object-first video_* pattern, and names like agent_me, chat_completions, and funding_instructions break the dominant convention.
At 18 tools, the surface is on the heavy side, and the count is inflated by lower-level variants that duplicate agent-facing tools such as video_queue vs generate_video and video_retrieve vs get_generation_status. A leaner set could consolidate these while still covering account, key, model, image, and video workflows.
The set covers the account/key lifecycle, funding and price controls, model discovery, chat, image generation, and a full video quote/queue/status/retrieve/cleanup flow. It also provides request-trace recovery and capacity checks, so agents have no obvious dead ends for the stated domain.